Data Operations Engineer
Personify Health · United States · 3 wk ago
RemoteRemoteEngineering$84k–$87k/yrFull-time
We need to output HTML fragment with sections: h3 headings for sections present: Overview? The instruction: Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Do NOT repeat the job title as a heading. We need to include sections only when posting has real specific content. The posting includes Overview (Who We Are), Responsibilities, Qualifications, Work Environment, Benefits, Compensation (Pay). Also maybe "Nice To Have" could be part of Qualifications or Skills. We should combine similar sections.
We need to preserve all substantive info, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. Also remove "Disclaimer", "Work Environment" maybe keep as it's substantive? It's about diversity etc. Could be considered a section but not in list of allowed headings; but we could maybe put under "Overview" or "About the role". However instruction says use h3 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 map content to those headings.
We have:
- Overview / Who We Are: description of company and mission. Could be "About the role" or maybe "Overview". Since they said e.g. About the role, we can use "About the role". But the overview is about company, not role. Could still use "About the role". Might be okay.
- Responsibilities: clearly present.
- Qualifications: includes Required Knowledge, Skills, And Abilities and Nice To Have. Could be "Qualifications". Also we could separate Skills but better to keep Qualifications.
- Benefits: present.
- Pay: compensation range.
- Schedule: not mentioned. So omit.
- Requirements: maybe same as Qualifications. We'll not duplicate.
We need to avoid filler like "commensurate with experience". Not present.
We need to remove boilerplate: "Disclaimer", "Work Environment" maybe keep as a paragraph under Overview? But it's about diversity; could be part of "About the role" or separate section "Work Environment". Since not in list, maybe we incorporate into Overview.
Also remove "Stay Safe" etc.
We need to preserve all substantive info: include details about responsibilities, qualifications, benefits, compensation.
Let's extract sections:
Overview / Who We Are:
"Because health is personal. That's why Personify Health created the first and only personalized health platform—bringing health plan administration, holistic wellbeing solutions, and comprehensive care navigation together in one place. We serve employers, health plans, and health systems with data-driven solutions that reduce costs while actually improving health outcomes. Together, our team is on a mission to empower people to lead healthier lives. This role is On-Site in Tempe, AZ Learn even more about the work that drives us at personifyhealth.com."
We should keep that.
Responsibilities:
List bullet points from "What You'll Actually Do" and the paragraph after.
Responsibilities content:
- Data Operations Engineer supports the development and maintenance of data systems used in healthcare and TPA claims processing.
- Assists with building and troubleshooting data pipelines, ensuring data accuracy across on-prem and cloud environments, and collaborating with senior engineers, analysts, and business teams.
- Approximately 50% of the role involves handling support tickets, including diagnosing pipeline issues, addressing data quality concerns, and responding to user requests.
- This position is ideal for someone early in their data engineering career with minimum 2 years of experience who is eager to learn and grow technical skills in ETL/ELT, SQL, and data workflows while contributing to operational and analytical needs across the organization.
Then under Qualifications there is "Essential Functions/Responsibilities/Duties" which repeats many duties; we should not duplicate. We'll keep responsibilities as above; maybe incorporate the essential functions as part of responsibilities but avoid duplication. The essential functions list is quite detailed; we should preserve that info but not duplicate. Since responsibilities already covered some, we can merge the essential functions into responsibilities as additional bullet points, ensuring we don't repeat same sentences.
Let's extract essential functions bullet points:
- Assist in maintaining and troubleshooting ETL/ELT data pipelines used for healthcare and TPA claims processing.
- Work with Python and SQL to support data extraction, transformation, validation, and loading across on-prem and cloud environments.
- Help monitor pipeline performance and resolve data issues, including reviewing logs, investigating failed jobs, and correcting data discrepancies.
- Handle support tickets (~50% of the time), responding to user requests, researching data questions, and helping resolve operational data problems.
- Supports daily process monitoring, including checking production processes and/or jobs, application performance, application maintenance, etc.
- Support data management tasks in systems such as PostgreSQL, Oracle, and cloud-based databases.
- Work with senior team members to learn data workflows, healthcare data formats, file transfers, and reporting processes.
- Assist in maintaining data quality and accuracy through routine checks, documentation, and follow-up.
- Collaborate with Data Analysts, Developers, and business users to understand data needs and support ongoing reporting and data operations.
- Participate in team meetings, sprint activities, and knowledge-sharing to continue developing data engineering skills.
These are more detailed; we should include them under Responsibilities (maybe as bullet list). Ensure not to duplicate the earlier generic statements. We can combine.
Qualifications:
Required Knowledge, Skills, And Abilities:
- AWS Certification (or willingness to obtain within 6–12 months), such as AWS Cloud Practitioner or AWS Developer – Associate.
- 2–3 years of experience in data engineering, analytics engineering, or a related technical role.
- Proficiency in Python and SQL, including writing queries, joins, basic transformations, and troubleshooting.
- Hands-on experience with relational databases (PostgreSQL, Oracle, AWS RDS) and familiarity with basic data warehouse concepts.
- Some exposure to cloud environments (AWS, Azure, ) is preferred but not required.
- Understanding of ETL/ELT pipelines, data validation, and data quality monitoring.
- Experience handling support tickets or operational data issues is strongly preferred (~50% of role).
- Basic knowledge of Linux command line for navigating servers and running scripts.
- Familiarity with collaboration tools such as JIRA and Git/Bitbucket.
- Strong attention to detail and focus on data accuracy and reliability.
- Effective written and verbal communication skills; able to document findings and processes.
- Demonstrated ability to manage time, prioritize tasks, and follow through on commitments.
- Collaborative mindset, able to work with both technical and non-technical team members.
- Self-motivated, able to prioritize tasks, and eager to learn from senior team members.
- Interest in developing skills in ETL workflows, data pipelines, and cloud data environments over time.
Nice To Have (Not Required):
- Experience with healthcare EDI formats (e.g., 834, 835, 837, 999).
- Exposure to AWS services (e.g., S3, RDS, Lambda) or cloud-based data tools.
- Experience with orchestration tools (Airflow), containers (Docker), or CI/CD pipelines.
- Familiarity with relational databases such as PostgreSQL, Oracle, or AWS RDS.
- Familiarity with AWS services (S3, RDS, Lambda, Glue) or modern data warehouses (Redshift, Snowflake).
- Basic understanding of data modeling concepts (star/snowflake schemas, dimensional modeling).
We can combine Nice To Have under Qualifications as a subsection maybe as a bullet list under "Preferred Qualifications". But instruction only says use h3 for section headings; we can still have ul li inside.
Benefits:
- Competitive base salary and benefits effective day one
- Comprehensive medical and dental through our own health solutions (yes, we use what we build)
- Unlimited PTO—rest and recharge time is non-negotiable
- Mental health support, retirement planning, and financial protection
- Professional development with clear career progression and learning budgets
- Mission-driven culture where diverse perspectives drive real impact on people's health
- Want the full picture? Visit personifyhealthbenefits.com to explore our complete benefits package, wellness programs, and other employee perks.
Compensation/Pay:
- This position offers a base salary range of $84,000-$87,000, depending on location, skills, and experience.
- You're eligible for our full benefits package starting day one.
We could make a Pay section with that.
Schedule: not present.
We should also include location: On-Site in Tempe, AZ maybe as part of Overview.
We must not include boilerplate like "Disclaimer", "Work Environment", "Stay Safe", "Our Commitment", "EEO", etc.
We need to output only HTML fragment.
Let's structure:
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Do NOT repeat the job title as a heading. We need to include sections only when posting has real specific content. The posting includes Overview (Who We Are), Responsibilities, Qualifications, Work Environment, Benefits, Compensation (Pay). Also maybe "Nice To Have" could be part of Qualifications or Skills. We should combine similar sections.
We need to preserve all substantive info, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. Also remove "Disclaimer", "Work Environment" maybe keep as it's substantive? It's about diversity etc. Could be considered a section but not in list of allowed headings; but we could maybe put under "Overview" or "About the role". However instruction says use h3 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 map content to those headings.
We have:
- Overview / Who We Are: description of company and mission. Could be "About the role" or maybe "Overview". Since they said e.g. About the role, we can use "About the role". But the overview is about company, not role. Could still use "About the role". Might be okay.
- Responsibilities: clearly present.
- Qualifications: includes Required Knowledge, Skills, And Abilities and Nice To Have. Could be "Qualifications". Also we could separate Skills but better to keep Qualifications.
- Benefits: present.
- Pay: compensation range.
- Schedule: not mentioned. So omit.
- Requirements: maybe same as Qualifications. We'll not duplicate.
We need to avoid filler like "commensurate with experience". Not present.
We need to remove boilerplate: "Disclaimer", "Work Environment" maybe keep as a paragraph under Overview? But it's about diversity; could be part of "About the role" or separate section "Work Environment". Since not in list, maybe we incorporate into Overview.
Also remove "Stay Safe" etc.
We need to preserve all substantive info: include details about responsibilities, qualifications, benefits, compensation.
Let's extract sections:
Overview / Who We Are:
"Because health is personal. That's why Personify Health created the first and only personalized health platform—bringing health plan administration, holistic wellbeing solutions, and comprehensive care navigation together in one place. We serve employers, health plans, and health systems with data-driven solutions that reduce costs while actually improving health outcomes. Together, our team is on a mission to empower people to lead healthier lives. This role is On-Site in Tempe, AZ Learn even more about the work that drives us at personifyhealth.com."
We should keep that.
Responsibilities:
List bullet points from "What You'll Actually Do" and the paragraph after.
Responsibilities content:
- Data Operations Engineer supports the development and maintenance of data systems used in healthcare and TPA claims processing.
- Assists with building and troubleshooting data pipelines, ensuring data accuracy across on-prem and cloud environments, and collaborating with senior engineers, analysts, and business teams.
- Approximately 50% of the role involves handling support tickets, including diagnosing pipeline issues, addressing data quality concerns, and responding to user requests.
- This position is ideal for someone early in their data engineering career with minimum 2 years of experience who is eager to learn and grow technical skills in ETL/ELT, SQL, and data workflows while contributing to operational and analytical needs across the organization.
Then under Qualifications there is "Essential Functions/Responsibilities/Duties" which repeats many duties; we should not duplicate. We'll keep responsibilities as above; maybe incorporate the essential functions as part of responsibilities but avoid duplication. The essential functions list is quite detailed; we should preserve that info but not duplicate. Since responsibilities already covered some, we can merge the essential functions into responsibilities as additional bullet points, ensuring we don't repeat same sentences.
Let's extract essential functions bullet points:
- Assist in maintaining and troubleshooting ETL/ELT data pipelines used for healthcare and TPA claims processing.
- Work with Python and SQL to support data extraction, transformation, validation, and loading across on-prem and cloud environments.
- Help monitor pipeline performance and resolve data issues, including reviewing logs, investigating failed jobs, and correcting data discrepancies.
- Handle support tickets (~50% of the time), responding to user requests, researching data questions, and helping resolve operational data problems.
- Supports daily process monitoring, including checking production processes and/or jobs, application performance, application maintenance, etc.
- Support data management tasks in systems such as PostgreSQL, Oracle, and cloud-based databases.
- Work with senior team members to learn data workflows, healthcare data formats, file transfers, and reporting processes.
- Assist in maintaining data quality and accuracy through routine checks, documentation, and follow-up.
- Collaborate with Data Analysts, Developers, and business users to understand data needs and support ongoing reporting and data operations.
- Participate in team meetings, sprint activities, and knowledge-sharing to continue developing data engineering skills.
These are more detailed; we should include them under Responsibilities (maybe as bullet list). Ensure not to duplicate the earlier generic statements. We can combine.
Qualifications:
Required Knowledge, Skills, And Abilities:
- AWS Certification (or willingness to obtain within 6–12 months), such as AWS Cloud Practitioner or AWS Developer – Associate.
- 2–3 years of experience in data engineering, analytics engineering, or a related technical role.
- Proficiency in Python and SQL, including writing queries, joins, basic transformations, and troubleshooting.
- Hands-on experience with relational databases (PostgreSQL, Oracle, AWS RDS) and familiarity with basic data warehouse concepts.
- Some exposure to cloud environments (AWS, Azure, ) is preferred but not required.
- Understanding of ETL/ELT pipelines, data validation, and data quality monitoring.
- Experience handling support tickets or operational data issues is strongly preferred (~50% of role).
- Basic knowledge of Linux command line for navigating servers and running scripts.
- Familiarity with collaboration tools such as JIRA and Git/Bitbucket.
- Strong attention to detail and focus on data accuracy and reliability.
- Effective written and verbal communication skills; able to document findings and processes.
- Demonstrated ability to manage time, prioritize tasks, and follow through on commitments.
- Collaborative mindset, able to work with both technical and non-technical team members.
- Self-motivated, able to prioritize tasks, and eager to learn from senior team members.
- Interest in developing skills in ETL workflows, data pipelines, and cloud data environments over time.
Nice To Have (Not Required):
- Experience with healthcare EDI formats (e.g., 834, 835, 837, 999).
- Exposure to AWS services (e.g., S3, RDS, Lambda) or cloud-based data tools.
- Experience with orchestration tools (Airflow), containers (Docker), or CI/CD pipelines.
- Familiarity with relational databases such as PostgreSQL, Oracle, or AWS RDS.
- Familiarity with AWS services (S3, RDS, Lambda, Glue) or modern data warehouses (Redshift, Snowflake).
- Basic understanding of data modeling concepts (star/snowflake schemas, dimensional modeling).
We can combine Nice To Have under Qualifications as a subsection maybe as a bullet list under "Preferred Qualifications". But instruction only says use h3 for section headings; we can still have ul li inside.
Benefits:
- Competitive base salary and benefits effective day one
- Comprehensive medical and dental through our own health solutions (yes, we use what we build)
- Unlimited PTO—rest and recharge time is non-negotiable
- Mental health support, retirement planning, and financial protection
- Professional development with clear career progression and learning budgets
- Mission-driven culture where diverse perspectives drive real impact on people's health
- Want the full picture? Visit personifyhealthbenefits.com to explore our complete benefits package, wellness programs, and other employee perks.
Compensation/Pay:
- This position offers a base salary range of $84,000-$87,000, depending on location, skills, and experience.
- You're eligible for our full benefits package starting day one.
We could make a Pay section with that.
Schedule: not present.
We should also include location: On-Site in Tempe, AZ maybe as part of Overview.
We must not include boilerplate like "Disclaimer", "Work Environment", "Stay Safe", "Our Commitment", "EEO", etc.
We need to output only HTML fragment.
Let's structure:
About the role
Because health is personal. That's why Personify Health created the first and only personalized health platform—bringing health plan administration, holistic wellbeing solutions, and comprehensive care navigation together in one place. We serve employers, health plans, and health systems with data-driven solutions that reduce costs while actually improving health outcomes. Together, our team is on a mission to empower people to lead healthier lives. This role is On-Site in Tempe, AZ. Learn even more about the work that drives us at personifyhealth.com.
Responsibilities
- Assist in maintaining and troubleshooting ETL/ELT data pipelines used for healthcare and TPA claims processing.
- Work with Python and SQL to support data extraction, transformation, validation, and loading across on-prem and cloud environments.
- Help monitor pipeline performance and resolve data issues, including reviewing logs, investigating failed jobs, and correcting data discrepancies.
- Handle support tickets (~50% of the time), responding to user requests, researching data questions, and helping resolve operational data problems.
- Support daily process monitoring, including checking production processes and/or jobs, application performance, application maintenance, etc.
- Support data management tasks in systems such as PostgreSQL, Oracle, and cloud-based databases.
- Work with senior team members to learn data workflows, healthcare data formats, file transfers, and reporting processes.
- Assist in maintaining data quality and accuracy through routine checks, documentation, and follow-up.
- Collaborate with Data Analysts, Developers, and business users to understand data needs and support ongoing reporting and data operations.
- Participate in team meetings, sprint activities, and knowledge-sharing to continue developing data engineering skills.
- Approximately 50% of the role involves handling support tickets, including diagnosing pipeline issues, addressing data quality concerns, and responding to user requests.
- This position is ideal for someone early in their data engineering career with minimum 2 years of experience who is eager to learn and grow technical skills in ETL/ELT, SQL, and data workflows while contributing to operational and analytical needs across the organization.