Lead Data Engineer - Healthcare Data & Audience Applications
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We need to preserve all substantive info, not invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions.
We need to include a section ONLY when posting has real, specific content for it. So we need sections: About the role? Actually "Who We Are" is company description; could be "About the company" but not listed as allowed headings. Allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should map content to those headings where appropriate. "Who We Are" could be "About the role"? Not exactly. Maybe we can treat "Who We Are" as "About the role"? But that seems odd. However we could also omit that section if not matching allowed headings? The instruction: "use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but suggests using those. Probably we should use those headings for sections we have. Let's map:
- About the role: could contain "Role Overview" and maybe "Who We Are"? Actually "About the role" is about the role, not company. So we can put Role Overview there.
- Responsibilities: Key Responsibilities.
- Requirements: Qualifications? Or Requirements could be qualifications. But we also have "Engineering Expectations" and "Healthcare & Domain Expectations" which are more like skills/requirements. Could combine into Requirements or Skills. The allowed headings include Requirements, Qualifications, Skills. We need to decide.
We have Qualifications section already. So we can use Qualifications
for the Qualifications bullet list.
We have Engineering Expectations and Healthcare & Domain Expectations: these are skills/requirements. Could put under Skills
or Requirements
. Since we already have Qualifications, maybe Skills is appropriate for those expectations.
We have Benefits & Perks: map to Benefits.
We have SALARY RANGE: map to Pay.
Schedule: not present, so omit.
We also have "What You’ll Build": could be part of About the role or Responsibilities? Might be better as part of About the role (description of what you'll build). Could also be Responsibilities? But it's more about what you'll build. I'd put it under About the role.
Thus sections:
About the role
: include Who We Are? Actually Who We Are is company description; maybe we can include that as part of About the role? But it's not about the role. However we could still include it as prose under About the role? Might be odd but acceptable. Alternatively we could create a separate section not in allowed list? The instruction says use those headings for section headings (e.g...). It doesn't strictly forbid other headings, but says "use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." Likely they expect us to use those headings only. So we need to fit all content into those headings.
Thus we need to distribute:
- About the role: include Role Overview and What You’ll Build (maybe also Who We Are? but that's company info; maybe we can include it as part of About the role as context). We'll include Who We Are as a brief paragraph.
- Responsibilities: Key Responsibilities.
- Requirements: maybe combine Engineering Expectations and Healthcare & Domain Expectations? Or we could use Requirements for those and Qualifications for the qualifications list. Let's do:
Requirements
: include Engineering Expectations and Healthcare & Domain Expectations (these are expectations/skills). Could be bullet lists.
Qualifications
: the Qualifications bullet list.
Benefits
: Benefits & Perks.
Pay
: SALARY RANGE.
We must not include Schedule.
We must not include any boilerplate like EEO, People & Culture, ZETA IN THE NEWS.
We must preserve all substantive info: ensure we don't lose any details.
We need to format lists as - . For prose, use
.
We need to avoid repeating content.
Let's extract content.
Who We Are paragraph:
"Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com."
We can keep that as prose.
Role Overview paragraph:
"Zeta Global is seeking a Lead Data Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows. This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability. The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments."
What You’ll Build bullet list:
- Applications supporting HCP and patient / direct-to-consumer (DTC) audience discovery, segmentation, and activation
- Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
- Identity resolution and data linkage services across fragmented data sources
- Reporting, attribution, and measurement systems connecting campaigns to outcomes
- APIs and services enabling downstream activation, analytics, and partner integrations
- Healthcare Cloud and data-mapping architecture across claims/Rx, NPI/HCP, patient, media-exposure, brand, and connector datasets.
- Healthcare-specific semantic cubes, governed views, data contracts, and domain APIs consumed by Vertical Apps; front-end applications should consume stable domain APIs rather than query raw stores or Cube directly.
- Identity resolution, match-rate measurement, medical-code mapping, and approved joins under CERT/HIPAA rules.
- Foundational data products for NPI onboarding, PLD reporting, script reporting, HCP/Patient intelligence, journeys, and Next Best Action.
Key Responsibilities bullet list:
- Define and maintain the healthcare data architecture, interface contracts, ADRs, schemas, and staged delivery plan.
- Lead ingestion and transformation patterns across Snowflake, Athena/S3, MySQL, and approved healthcare stores without duplicating shared platform capabilities.
- Partner with Data Cloud on source certification, partner-feed contracts, identity validation, raw-zone ownership, and data availability SLAs.
- Design healthcare base/vertical models and published/governed views, with row/member-level controls, account scoping, masking, and backward-compatible versioning.
- Set SLOs and operational readiness criteria; ensure dashboards, alerts, runbooks, rollback paths, and incident ownership are in place before release.
- Lead design and code reviews, mentor the Senior Data Engineer, and coordinate dependencies across the pod.
- Support compliance evidence, annual audits, US data-residency controls, and stoplight decisions: Start, Stop, or Requires CERT.
- Apply privacy-by-design principles across all systems handling PHI/PII
- Partner with Product and Data teams to translate healthcare requirements into scalable architectures
- Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
Engineering Expectations bullet list:
- Strong experience designing distributed systems, including microservices and event-driven architectures
- Deep understanding of data modeling, storage systems (OLTP and OLAP), and data-processing frameworks
- Experience with streaming and batch processing technologies, such as Kafka, Spark, Flink, or similar tools
- Proficiency in backend development using Python, Java, or Ruby, as well as API design using REST or gRPC
- Experience with workflow orchestration tools, such as Apache Airflow
- Experience working with data warehouses and lakehouse platforms, such as Snowflake, Databricks, or similar technologies
- Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code
- Familiarity with containerization and orchestration technologies, including Docker and Kubernetes
- Experience implementing observability practices, including logging, metrics, and tracing, as well as reliability patterns
- Strong understanding of performance optimization and scalability trade-offs
Healthcare & Domain Expectations bullet list:
- Experience working with HCP data (provider identity, targeting, segmentation)
- Experience with patient / DTC data workflows and privacy-aware systems
- Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
- Familiarity with identity graphs and data onboarding patterns
- Experience building reporting or attribution systems tied to business outcomes
- Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements
- Technical standards for lineage, data quality, access control, masking, retention, auditability, observability, and cost.
Qualifications bullet list:
- 8+ years of data engineering experience with increasing technical ownership
- Expert SQL and strong Python, Java; experience with batch and streaming patterns, orchestration, testing, and schema evolution.
- Proven track record of building and scaling data-intensive or distributed systems
- Experience working in regulated environments (healthcare strongly preferred)
- Strong system design and architecture skills
- Ability to lead technically while remaining hands-on in implementation
- Strong collaboration skills across engineering, product, and data teams
Preferred Experience bullet list (under Qualifications? Actually after Qualifications there is "Preferred Experience" with bullet points):
- Experience with healthcare data providers or identity ecosystems
- Background in AdTech, MarTech, or audience/data platforms
- Experience with privacy-enhancing technologies (tokenization, clean rooms)
- Exposure to ML/AI-driven data products or analytics systems
We should include those under Qualifications as part of qualifications (maybe as a sublist). We'll keep them as bullet points under Qualifications.
Benefits & Perks bullet list:
- Unlimited PTO
- Excellent medical, dental, and vision coverage
- Employee Equity
- Employee Discounts, Virtual Wellness Classes, and Pet Insurance
- And more!!
We can keep "And more!!" as a bullet.
Pay: "The salary range for this role is $180,000 - $200,000, depending on location and experience."
Now we need to output HTML fragment only.
Structure:
About the role
Who We Are ...
Role Overview ...
What You’ll Build items
Responsibilities
for prose. We need to preserve all substantive info, not invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. We need to include a section ONLY when posting has real, specific content for it. So we need sections: About the role? Actually "Who We Are" is company description; could be "About the company" but not listed as allowed headings. Allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should map content to those headings where appropriate. "Who We Are" could be "About the role"? Not exactly. Maybe we can treat "Who We Are" as "About the role"? But that seems odd. However we could also omit that section if not matching allowed headings? The instruction: "use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but suggests using those. Probably we should use those headings for sections we have. Let's map:
- About the role: could contain "Role Overview" and maybe "Who We Are"? Actually "About the role" is about the role, not company. So we can put Role Overview there.
- Responsibilities: Key Responsibilities.
- Requirements: Qualifications? Or Requirements could be qualifications. But we also have "Engineering Expectations" and "Healthcare & Domain Expectations" which are more like skills/requirements. Could combine into Requirements or Skills. The allowed headings include Requirements, Qualifications, Skills. We need to decide.
We have Qualifications section already. So we can use Qualifications
for the Qualifications bullet list.
We have Engineering Expectations and Healthcare & Domain Expectations: these are skills/requirements. Could put under Skills
or Requirements
. Since we already have Qualifications, maybe Skills is appropriate for those expectations.
We have Benefits & Perks: map to Benefits.
We have SALARY RANGE: map to Pay.
Schedule: not present, so omit.
We also have "What You’ll Build": could be part of About the role or Responsibilities? Might be better as part of About the role (description of what you'll build). Could also be Responsibilities? But it's more about what you'll build. I'd put it under About the role.
Thus sections:
About the role
: include Who We Are? Actually Who We Are is company description; maybe we can include that as part of About the role? But it's not about the role. However we could still include it as prose under About the role? Might be odd but acceptable. Alternatively we could create a separate section not in allowed list? The instruction says use those headings for section headings (e.g...). It doesn't strictly forbid other headings, but says "use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." Likely they expect us to use those headings only. So we need to fit all content into those headings.
Thus we need to distribute:
- About the role: include Role Overview and What You’ll Build (maybe also Who We Are? but that's company info; maybe we can include it as part of About the role as context). We'll include Who We Are as a brief paragraph.
- Responsibilities: Key Responsibilities.
- Requirements: maybe combine Engineering Expectations and Healthcare & Domain Expectations? Or we could use Requirements for those and Qualifications for the qualifications list. Let's do:
Requirements
: include Engineering Expectations and Healthcare & Domain Expectations (these are expectations/skills). Could be bullet lists.
Qualifications
: the Qualifications bullet list.
Benefits
: Benefits & Perks.
Pay
: SALARY RANGE.
We must not include Schedule.
We must not include any boilerplate like EEO, People & Culture, ZETA IN THE NEWS.
We must preserve all substantive info: ensure we don't lose any details.
We need to format lists as - . For prose, use
.
We need to avoid repeating content.
Let's extract content.
Who We Are paragraph:
"Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com."
We can keep that as prose.
Role Overview paragraph:
"Zeta Global is seeking a Lead Data Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows. This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability. The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments."
What You’ll Build bullet list:
- Applications supporting HCP and patient / direct-to-consumer (DTC) audience discovery, segmentation, and activation
- Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
- Identity resolution and data linkage services across fragmented data sources
- Reporting, attribution, and measurement systems connecting campaigns to outcomes
- APIs and services enabling downstream activation, analytics, and partner integrations
- Healthcare Cloud and data-mapping architecture across claims/Rx, NPI/HCP, patient, media-exposure, brand, and connector datasets.
- Healthcare-specific semantic cubes, governed views, data contracts, and domain APIs consumed by Vertical Apps; front-end applications should consume stable domain APIs rather than query raw stores or Cube directly.
- Identity resolution, match-rate measurement, medical-code mapping, and approved joins under CERT/HIPAA rules.
- Foundational data products for NPI onboarding, PLD reporting, script reporting, HCP/Patient intelligence, journeys, and Next Best Action.
Key Responsibilities bullet list:
- Define and maintain the healthcare data architecture, interface contracts, ADRs, schemas, and staged delivery plan.
- Lead ingestion and transformation patterns across Snowflake, Athena/S3, MySQL, and approved healthcare stores without duplicating shared platform capabilities.
- Partner with Data Cloud on source certification, partner-feed contracts, identity validation, raw-zone ownership, and data availability SLAs.
- Design healthcare base/vertical models and published/governed views, with row/member-level controls, account scoping, masking, and backward-compatible versioning.
- Set SLOs and operational readiness criteria; ensure dashboards, alerts, runbooks, rollback paths, and incident ownership are in place before release.
- Lead design and code reviews, mentor the Senior Data Engineer, and coordinate dependencies across the pod.
- Support compliance evidence, annual audits, US data-residency controls, and stoplight decisions: Start, Stop, or Requires CERT.
- Apply privacy-by-design principles across all systems handling PHI/PII
- Partner with Product and Data teams to translate healthcare requirements into scalable architectures
- Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
Engineering Expectations bullet list:
- Strong experience designing distributed systems, including microservices and event-driven architectures
- Deep understanding of data modeling, storage systems (OLTP and OLAP), and data-processing frameworks
- Experience with streaming and batch processing technologies, such as Kafka, Spark, Flink, or similar tools
- Proficiency in backend development using Python, Java, or Ruby, as well as API design using REST or gRPC
- Experience with workflow orchestration tools, such as Apache Airflow
- Experience working with data warehouses and lakehouse platforms, such as Snowflake, Databricks, or similar technologies
- Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code
- Familiarity with containerization and orchestration technologies, including Docker and Kubernetes
- Experience implementing observability practices, including logging, metrics, and tracing, as well as reliability patterns
- Strong understanding of performance optimization and scalability trade-offs
Healthcare & Domain Expectations bullet list:
- Experience working with HCP data (provider identity, targeting, segmentation)
- Experience with patient / DTC data workflows and privacy-aware systems
- Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
- Familiarity with identity graphs and data onboarding patterns
- Experience building reporting or attribution systems tied to business outcomes
- Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements
- Technical standards for lineage, data quality, access control, masking, retention, auditability, observability, and cost.
Qualifications bullet list:
- 8+ years of data engineering experience with increasing technical ownership
- Expert SQL and strong Python, Java; experience with batch and streaming patterns, orchestration, testing, and schema evolution.
- Proven track record of building and scaling data-intensive or distributed systems
- Experience working in regulated environments (healthcare strongly preferred)
- Strong system design and architecture skills
- Ability to lead technically while remaining hands-on in implementation
- Strong collaboration skills across engineering, product, and data teams
Preferred Experience bullet list (under Qualifications? Actually after Qualifications there is "Preferred Experience" with bullet points):
- Experience with healthcare data providers or identity ecosystems
- Background in AdTech, MarTech, or audience/data platforms
- Experience with privacy-enhancing technologies (tokenization, clean rooms)
- Exposure to ML/AI-driven data products or analytics systems
We should include those under Qualifications as part of qualifications (maybe as a sublist). We'll keep them as bullet points under Qualifications.
Benefits & Perks bullet list:
- Unlimited PTO
- Excellent medical, dental, and vision coverage
- Employee Equity
- Employee Discounts, Virtual Wellness Classes, and Pet Insurance
- And more!!
We can keep "And more!!" as a bullet.
Pay: "The salary range for this role is $180,000 - $200,000, depending on location and experience."
Now we need to output HTML fragment only.
Structure:
About the role
Who We Are ...
Role Overview ...
What You’ll Build items
Responsibilities
Qualifications
for the Qualifications bullet list. We have Engineering Expectations and Healthcare & Domain Expectations: these are skills/requirements. Could put underSkills
orRequirements
. Since we already have Qualifications, maybe Skills is appropriate for those expectations. We have Benefits & Perks: map to Benefits. We have SALARY RANGE: map to Pay. Schedule: not present, so omit. We also have "What You’ll Build": could be part of About the role or Responsibilities? Might be better as part of About the role (description of what you'll build). Could also be Responsibilities? But it's more about what you'll build. I'd put it under About the role. Thus sections:About the role
: include Who We Are? Actually Who We Are is company description; maybe we can include that as part of About the role? But it's not about the role. However we could still include it as prose under About the role? Might be odd but acceptable. Alternatively we could create a separate section not in allowed list? The instruction says use those headings for section headings (e.g...). It doesn't strictly forbid other headings, but says "use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." Likely they expect us to use those headings only. So we need to fit all content into those headings.
Thus we need to distribute:
- About the role: include Role Overview and What You’ll Build (maybe also Who We Are? but that's company info; maybe we can include it as part of About the role as context). We'll include Who We Are as a brief paragraph.
- Responsibilities: Key Responsibilities.
- Requirements: maybe combine Engineering Expectations and Healthcare & Domain Expectations? Or we could use Requirements for those and Qualifications for the qualifications list. Let's do:
Requirements
: include Engineering Expectations and Healthcare & Domain Expectations (these are expectations/skills). Could be bullet lists.
Qualifications
: the Qualifications bullet list.
Benefits
: Benefits & Perks.
Pay
: SALARY RANGE.
We must not include Schedule.
We must not include any boilerplate like EEO, People & Culture, ZETA IN THE NEWS.
We must preserve all substantive info: ensure we don't lose any details.
We need to format lists as - . For prose, use
.
We need to avoid repeating content.
Let's extract content.
Who We Are paragraph:
"Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com."
We can keep that as prose.
Role Overview paragraph:
"Zeta Global is seeking a Lead Data Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows. This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability. The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments."
What You’ll Build bullet list:
- Applications supporting HCP and patient / direct-to-consumer (DTC) audience discovery, segmentation, and activation
- Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
- Identity resolution and data linkage services across fragmented data sources
- Reporting, attribution, and measurement systems connecting campaigns to outcomes
- APIs and services enabling downstream activation, analytics, and partner integrations
- Healthcare Cloud and data-mapping architecture across claims/Rx, NPI/HCP, patient, media-exposure, brand, and connector datasets.
- Healthcare-specific semantic cubes, governed views, data contracts, and domain APIs consumed by Vertical Apps; front-end applications should consume stable domain APIs rather than query raw stores or Cube directly.
- Identity resolution, match-rate measurement, medical-code mapping, and approved joins under CERT/HIPAA rules.
- Foundational data products for NPI onboarding, PLD reporting, script reporting, HCP/Patient intelligence, journeys, and Next Best Action.
Key Responsibilities bullet list:
- Define and maintain the healthcare data architecture, interface contracts, ADRs, schemas, and staged delivery plan.
- Lead ingestion and transformation patterns across Snowflake, Athena/S3, MySQL, and approved healthcare stores without duplicating shared platform capabilities.
- Partner with Data Cloud on source certification, partner-feed contracts, identity validation, raw-zone ownership, and data availability SLAs.
- Design healthcare base/vertical models and published/governed views, with row/member-level controls, account scoping, masking, and backward-compatible versioning.
- Set SLOs and operational readiness criteria; ensure dashboards, alerts, runbooks, rollback paths, and incident ownership are in place before release.
- Lead design and code reviews, mentor the Senior Data Engineer, and coordinate dependencies across the pod.
- Support compliance evidence, annual audits, US data-residency controls, and stoplight decisions: Start, Stop, or Requires CERT.
- Apply privacy-by-design principles across all systems handling PHI/PII
- Partner with Product and Data teams to translate healthcare requirements into scalable architectures
- Drive engineering best practices across testing, CI/CD, code quality, and operational excellence
Engineering Expectations bullet list:
- Strong experience designing distributed systems, including microservices and event-driven architectures
- Deep understanding of data modeling, storage systems (OLTP and OLAP), and data-processing frameworks
- Experience with streaming and batch processing technologies, such as Kafka, Spark, Flink, or similar tools
- Proficiency in backend development using Python, Java, or Ruby, as well as API design using REST or gRPC
- Experience with workflow orchestration tools, such as Apache Airflow
- Experience working with data warehouses and lakehouse platforms, such as Snowflake, Databricks, or similar technologies
- Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code
- Familiarity with containerization and orchestration technologies, including Docker and Kubernetes
- Experience implementing observability practices, including logging, metrics, and tracing, as well as reliability patterns
- Strong understanding of performance optimization and scalability trade-offs
Healthcare & Domain Expectations bullet list:
- Experience working with HCP data (provider identity, targeting, segmentation)
- Experience with patient / DTC data workflows and privacy-aware systems
- Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
- Familiarity with identity graphs and data onboarding patterns
- Experience building reporting or attribution systems tied to business outcomes
- Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements
- Technical standards for lineage, data quality, access control, masking, retention, auditability, observability, and cost.
Qualifications bullet list:
- 8+ years of data engineering experience with increasing technical ownership
- Expert SQL and strong Python, Java; experience with batch and streaming patterns, orchestration, testing, and schema evolution.
- Proven track record of building and scaling data-intensive or distributed systems
- Experience working in regulated environments (healthcare strongly preferred)
- Strong system design and architecture skills
- Ability to lead technically while remaining hands-on in implementation
- Strong collaboration skills across engineering, product, and data teams
Preferred Experience bullet list (under Qualifications? Actually after Qualifications there is "Preferred Experience" with bullet points):
- Experience with healthcare data providers or identity ecosystems
- Background in AdTech, MarTech, or audience/data platforms
- Experience with privacy-enhancing technologies (tokenization, clean rooms)
- Exposure to ML/AI-driven data products or analytics systems
We should include those under Qualifications as part of qualifications (maybe as a sublist). We'll keep them as bullet points under Qualifications.
Benefits & Perks bullet list:
- Unlimited PTO
- Excellent medical, dental, and vision coverage
- Employee Equity
- Employee Discounts, Virtual Wellness Classes, and Pet Insurance
- And more!!
We can keep "And more!!" as a bullet.
Pay: "The salary range for this role is $180,000 - $200,000, depending on location and experience."
Now we need to output HTML fragment only.
Structure:
About the role
Who We Are ...
Role Overview ...
What You’ll Build items
Responsibilities
. We need to avoid repeating content. Let's extract content. Who We Are paragraph: "Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com." We can keep that as prose. Role Overview paragraph: "Zeta Global is seeking a Lead Data Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows. This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints. You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability. The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments." What You’ll Build bullet list: - Applications supporting HCP and patient / direct-to-consumer (DTC) audience discovery, segmentation, and activation - Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets - Identity resolution and data linkage services across fragmented data sources - Reporting, attribution, and measurement systems connecting campaigns to outcomes - APIs and services enabling downstream activation, analytics, and partner integrations - Healthcare Cloud and data-mapping architecture across claims/Rx, NPI/HCP, patient, media-exposure, brand, and connector datasets. - Healthcare-specific semantic cubes, governed views, data contracts, and domain APIs consumed by Vertical Apps; front-end applications should consume stable domain APIs rather than query raw stores or Cube directly. - Identity resolution, match-rate measurement, medical-code mapping, and approved joins under CERT/HIPAA rules. - Foundational data products for NPI onboarding, PLD reporting, script reporting, HCP/Patient intelligence, journeys, and Next Best Action. Key Responsibilities bullet list: - Define and maintain the healthcare data architecture, interface contracts, ADRs, schemas, and staged delivery plan. - Lead ingestion and transformation patterns across Snowflake, Athena/S3, MySQL, and approved healthcare stores without duplicating shared platform capabilities. - Partner with Data Cloud on source certification, partner-feed contracts, identity validation, raw-zone ownership, and data availability SLAs. - Design healthcare base/vertical models and published/governed views, with row/member-level controls, account scoping, masking, and backward-compatible versioning. - Set SLOs and operational readiness criteria; ensure dashboards, alerts, runbooks, rollback paths, and incident ownership are in place before release. - Lead design and code reviews, mentor the Senior Data Engineer, and coordinate dependencies across the pod. - Support compliance evidence, annual audits, US data-residency controls, and stoplight decisions: Start, Stop, or Requires CERT. - Apply privacy-by-design principles across all systems handling PHI/PII - Partner with Product and Data teams to translate healthcare requirements into scalable architectures - Drive engineering best practices across testing, CI/CD, code quality, and operational excellence Engineering Expectations bullet list: - Strong experience designing distributed systems, including microservices and event-driven architectures - Deep understanding of data modeling, storage systems (OLTP and OLAP), and data-processing frameworks - Experience with streaming and batch processing technologies, such as Kafka, Spark, Flink, or similar tools - Proficiency in backend development using Python, Java, or Ruby, as well as API design using REST or gRPC - Experience with workflow orchestration tools, such as Apache Airflow - Experience working with data warehouses and lakehouse platforms, such as Snowflake, Databricks, or similar technologies - Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code - Familiarity with containerization and orchestration technologies, including Docker and Kubernetes - Experience implementing observability practices, including logging, metrics, and tracing, as well as reliability patterns - Strong understanding of performance optimization and scalability trade-offs Healthcare & Domain Expectations bullet list: - Experience working with HCP data (provider identity, targeting, segmentation) - Experience with patient / DTC data workflows and privacy-aware systems - Understanding of healthcare data ecosystems (claims, provider, or audience datasets) - Familiarity with identity graphs and data onboarding patterns - Experience building reporting or attribution systems tied to business outcomes - Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements - Technical standards for lineage, data quality, access control, masking, retention, auditability, observability, and cost. Qualifications bullet list: - 8+ years of data engineering experience with increasing technical ownership - Expert SQL and strong Python, Java; experience with batch and streaming patterns, orchestration, testing, and schema evolution. - Proven track record of building and scaling data-intensive or distributed systems - Experience working in regulated environments (healthcare strongly preferred) - Strong system design and architecture skills - Ability to lead technically while remaining hands-on in implementation - Strong collaboration skills across engineering, product, and data teams Preferred Experience bullet list (under Qualifications? Actually after Qualifications there is "Preferred Experience" with bullet points): - Experience with healthcare data providers or identity ecosystems - Background in AdTech, MarTech, or audience/data platforms - Experience with privacy-enhancing technologies (tokenization, clean rooms) - Exposure to ML/AI-driven data products or analytics systems We should include those under Qualifications as part of qualifications (maybe as a sublist). We'll keep them as bullet points under Qualifications. Benefits & Perks bullet list: - Unlimited PTO - Excellent medical, dental, and vision coverage - Employee Equity - Employee Discounts, Virtual Wellness Classes, and Pet Insurance - And more!! We can keep "And more!!" as a bullet. Pay: "The salary range for this role is $180,000 - $200,000, depending on location and experience." Now we need to output HTML fragment only. Structure:
About the role
Who We Are ...
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- What You’ll Build items