Analytics Engineer
for each section heading. Use - for any list of duties/requirements/benefits, and
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate, navigation, legal, EEO, etc. Preserve all substantive info. Include a section only when posting has real specific content for it. So we need to extract sections.
From posting:
- Who We Are (company description) maybe "About the role"? Actually "Who We Are" is about company. Could be "About the role"? The instruction: use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content to these headings.
We have:
- Who We Are: description of company. Could go under "About the role"? Usually "About the role" is about the job, but we have "Who We Are" describing company. Could treat as "About the role"? Might be okay. Or we could create a section "About the role" with that content.
- The Opportunity: description of role. Could also be part of "About the role". Might combine.
- Responsibilities: list bullet points.
- Basic Qualifications: list.
- Nice to Have / Bonus Qualifications: list.
- Moxxi Values & Competencies: list.
- Salary Range: pay.
- Location: New York City (maybe schedule? Not schedule). Could be location but not required heading. Could embed in a short
maybe under "About the role"? Or we could create a "Schedule" section? Not present. No schedule info. So we should not create Schedule section.
- Benefits: not mentioned. So we should not create Benefits section.
- Skills: maybe we could extract from qualifications? But we have separate sections for Requirements, Qualifications, Skills. The posting has Basic Qualifications and Nice to Have. Could map Basic Qualifications to "Requirements" or "Qualifications". Nice to Have to "Skills". Or we could have Requirements = Basic Qualifications, Qualifications = Nice to Have? But we need to follow instruction: use headings as given. We need to include a section only when posting has real specific content for it. So we need to decide which sections we have content for.
We have content for:
- About the role (company description + opportunity). We'll put that.
- Responsibilities (list).
- Requirements (Basic Qualifications).
- Qualifications (Nice to Have / Bonus Qualifications). Or maybe Skills.
- Skills (maybe we could extract from values? But values are not skills. Could treat Moxxi Values & Competencies as "Skills"? Not exactly. Could treat as "Skills" but it's values. Might be better to put under "Skills" as they are competencies. However instruction: Use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we have to pick which to use. We have content for Requirements (Basic Qualifications). We have content for Qualifications (Nice to Have). We have content for Skills? Not explicitly but we could put Moxxi Values & Competencies under Skills. Or we could omit Skills if no specific skill list. But we have values/competencies which are somewhat skill-like. I'd include Skills section with those values.
- Pay: Salary Range.
- Schedule: none, so omit.
- Benefits: none, omit.
Thus output sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Pay.
Make sure each heading is
. Use
for prose,
- for lists.
We need to preserve all substantive information, not invent or summarize away detail. So we need to include all details from each section.
Let's extract content.
About the role: combine "Who We Are" and "The Opportunity". Must preserve all details.
Who We Are paragraph:
"At Moxxi, we’re redefining performance marketing with cutting-edge technology and a relentless focus on results. As a profitable, bootstrapped start-up, we are led by a team of industry veterans in performance marketing, ad tech, and digital publishing. Together, we’re building the premier platform to incubate, scale, and optimize digitally born businesses, setting new standards for data-driven success. Our entrepreneurial team brings proven experience from both global corporations and fast-growing startups. We’re passionate about delivering scalable, profitable outcomes for our partners through advanced profiling, targeting, and continuous optimization. Joining Moxxi means becoming part of a growing start-up in the heart of NYC, where you’ll have the opportunity to accelerate your career, expand your skill set, and shape the future of performance marketing. Location: New York City Level: Mid-level, 3 to 5 years experience"
The Opportunity paragraph:
"As an Analytics Engineer at Moxxi, you will build and own the data models behind our marketplace reporting, and you will use them to answer questions the business has not yet figured out how to ask. This is a small analytics team, so you will not be handed a queue of tickets. You will work directly with account managers, yield, and product to understand what is actually happening in the business, then build the models and reporting that make those answers repeatable. A significant part of this role is applying LLMs to analytics work: connecting models to the warehouse, engineering the context they need to be useful, and building the evals that tell you whether the output can be trusted. Our Analytics Lead owns this area, and you will be a key contributor to it. Moxxi owns its ad server, CMS, user journey orchestration, and SMS platform, so we generate our own data and can change the systems that produce it. That also means analytics here covers both sides of the business. You will report on marketplace performance, and you will measure what product ships: how a change to a user journey affects conversion, whether a new feature did what we expected, and what that tells us to build next. You will be joining shortly after a platform migration, so expect to help define and instrument the events behind that work rather than inherit a mature measurement stack. Over time, we expect this role to grow into quantitative work on how we model and select offers."
We need to keep all that. Could combine into a single
or multiple
. Probably multiple paragraphs okay.
Responsibilities: list bullet points after "Responsibilities". Let's extract:
- Own marketplace reporting across publishers, advertisers, and verticals, and make sure the numbers the business runs on are correct.
- Build and maintain dbt models in the warehouse, with tests, in version control, shipped to production.
- Investigate anomalies end to end: what moved, why it moved, and what we should do about it.
- Apply LLMs to analytics workflows, including context engineering and evaluation, in partnership with the Analytics Lead.
- Measure product work: define success metrics for new features and journey changes, specify the events needed to track them, and report back on whether the change did what we expected.
- Partner with operators to define KPIs so the business argues about decisions rather than about whose number is right.
- Build self-service reporting so routine questions stop routing through the analytics team.
- Own data quality: reconciliation across sources, and validation that catches problems before consumers do.
- Support experimentation and measurement design as we roll out platform and product changes.
- Grow into quantitative optimization work, including improving how we model and select what offers and experiences we serve to each user session.
We need to keep each as
- .
Requirements (Basic Qualifications): list:
- 3 to 5 years of experience in analytics, analytics engineering, or data science.
- Hands-on experience building with LLMs against real data, including how you validated whether the output was trustworthy. Demos and prompt experimentation are not sufficient.
- Production experience with dbt: you have owned models, written tests, worked in Git, and shipped.
- Advanced SQL and working proficiency in Python.
- Experience with a cloud data warehouse (BigQuery preferred, Snowflake or Redshift acceptable).
- Practical experience with data quality work: reconciliation across sources, and validating your own output.
- The ability to hold a business conversation. You should be able to walk us through a question you chased end to end, what you thought was happening, what you found, and what changed as a result.
- Comfort with ambiguity and a track record of deciding what to work on rather than waiting to be told.
Qualifications (Nice to Have / Bonus Qualifications): list:
- Experience in AdTech, performance marketing, or marketplace businesses.
- Experience as the first or only data person at a company.
- Product analytics experience: success metrics, event instrumentation, and measuring feature impact.
- Experimentation design and applied statistics.
- Exposure to bid optimization, yield management, or similar decision-modeling work.
- Familiarity with monitoring and observability tooling such as Datadog or Grafana.
Skills (Moxxi Values & Competencies): list:
- Self-Starter – You take initiative and solve problems before they become problems.
- Curious & Analytical – You ask why, dig deep into data, and experiment to learn what works.
- Efficiency-Oriented – Fast, focused, and action-driven.
- Relationship-Focused – You build trust and deliver value.
- Organized Multitasker – You thrive in fast-paced, high-velocity environments.
- Strategic Communicator – You translate performance into insight and insight into action.
Pay: Salary Range: $120,000 USD - $140,000 USD.
We should not include location as separate heading; could embed in About the role paragraph.
We must not include boilerplate like EEO etc. Not present.
Now produce HTML fragment.
We need to ensure no extra text outside HTML. Provide only HTML.
Let's craft:
About the role
At Moxxi, we’re redefining performance marketing with cutting-edge technology and a relentless focus on results. As a profitable, bootstrapped start-up, we are led by a team of industry veterans in performance marketing, ad tech, and digital publishing. Together, we’re building the premier platform to incubate, scale, and optimize digitally born businesses, setting new standards for data-driven success. Our entrepreneurial team brings proven experience from both global corporations and fast-growing startups. We’re passionate about delivering scalable, profitable outcomes for our partners through advanced profiling, targeting, and continuous optimization. Joining Moxxi means becoming part of a growing start-up in the heart of NYC, where you’ll have the opportunity to accelerate your career, expand your skill set, and shape the future of performance marketing. Location: New York City Level: Mid-level, 3 to 5 years experience
As an Analytics Engineer at Moxxi, you will build and own the data models behind our marketplace reporting, and you will use them to answer questions the business has not yet figured out how to ask. This is a small analytics team, so you will not be handed a queue of tickets. You will work directly with account managers, yield, and product to understand what is actually happening in the business, then build the models and reporting that make those answers repeatable. A significant part of this role is applying LLMs to analytics work: connecting models to the warehouse, engineering the context they need to be useful, and building the evals that tell you whether the output can be trusted. Our Analytics Lead owns this area, and you will be a key contributor to it. Moxxi owns its ad server, CMS, user journey orchestration, and SMS platform, so we generate our own data and can change the systems that produce it. That also means analytics here covers both sides of the business. You will report on marketplace performance, and you will measure what product ships: how a change to a user journey affects conversion, whether a new feature did what we expected, and what that tells us to build next. You will be joining shortly after a platform migration, so expect to help define and instrument the events behind that work rather than inherit a mature measurement stack. Over time, we expect this role to grow into quantitative work on
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate, navigation, legal, EEO, etc. Preserve all substantive info. Include a section only when posting has real specific content for it. So we need to extract sections. From posting: - Who We Are (company description) maybe "About the role"? Actually "Who We Are" is about company. Could be "About the role"? The instruction: use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content to these headings. We have: - Who We Are: description of company. Could go under "About the role"? Usually "About the role" is about the job, but we have "Who We Are" describing company. Could treat as "About the role"? Might be okay. Or we could create a section "About the role" with that content. - The Opportunity: description of role. Could also be part of "About the role". Might combine. - Responsibilities: list bullet points. - Basic Qualifications: list. - Nice to Have / Bonus Qualifications: list. - Moxxi Values & Competencies: list. - Salary Range: pay. - Location: New York City (maybe schedule? Not schedule). Could be location but not required heading. Could embed in a short
maybe under "About the role"? Or we could create a "Schedule" section? Not present. No schedule info. So we should not create Schedule section. - Benefits: not mentioned. So we should not create Benefits section. - Skills: maybe we could extract from qualifications? But we have separate sections for Requirements, Qualifications, Skills. The posting has Basic Qualifications and Nice to Have. Could map Basic Qualifications to "Requirements" or "Qualifications". Nice to Have to "Skills". Or we could have Requirements = Basic Qualifications, Qualifications = Nice to Have? But we need to follow instruction: use headings as given. We need to include a section only when posting has real specific content for it. So we need to decide which sections we have content for. We have content for: - About the role (company description + opportunity). We'll put that. - Responsibilities (list). - Requirements (Basic Qualifications). - Qualifications (Nice to Have / Bonus Qualifications). Or maybe Skills. - Skills (maybe we could extract from values? But values are not skills. Could treat Moxxi Values & Competencies as "Skills"? Not exactly. Could treat as "Skills" but it's values. Might be better to put under "Skills" as they are competencies. However instruction: Use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we have to pick which to use. We have content for Requirements (Basic Qualifications). We have content for Qualifications (Nice to Have). We have content for Skills? Not explicitly but we could put Moxxi Values & Competencies under Skills. Or we could omit Skills if no specific skill list. But we have values/competencies which are somewhat skill-like. I'd include Skills section with those values. - Pay: Salary Range. - Schedule: none, so omit. - Benefits: none, omit. Thus output sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Pay. Make sure each heading is
. Use
for prose,
- for lists.
We need to preserve all substantive information, not invent or summarize away detail. So we need to include all details from each section.
Let's extract content.
About the role: combine "Who We Are" and "The Opportunity". Must preserve all details.
Who We Are paragraph:
"At Moxxi, we’re redefining performance marketing with cutting-edge technology and a relentless focus on results. As a profitable, bootstrapped start-up, we are led by a team of industry veterans in performance marketing, ad tech, and digital publishing. Together, we’re building the premier platform to incubate, scale, and optimize digitally born businesses, setting new standards for data-driven success. Our entrepreneurial team brings proven experience from both global corporations and fast-growing startups. We’re passionate about delivering scalable, profitable outcomes for our partners through advanced profiling, targeting, and continuous optimization. Joining Moxxi means becoming part of a growing start-up in the heart of NYC, where you’ll have the opportunity to accelerate your career, expand your skill set, and shape the future of performance marketing. Location: New York City Level: Mid-level, 3 to 5 years experience"
The Opportunity paragraph:
"As an Analytics Engineer at Moxxi, you will build and own the data models behind our marketplace reporting, and you will use them to answer questions the business has not yet figured out how to ask. This is a small analytics team, so you will not be handed a queue of tickets. You will work directly with account managers, yield, and product to understand what is actually happening in the business, then build the models and reporting that make those answers repeatable. A significant part of this role is applying LLMs to analytics work: connecting models to the warehouse, engineering the context they need to be useful, and building the evals that tell you whether the output can be trusted. Our Analytics Lead owns this area, and you will be a key contributor to it. Moxxi owns its ad server, CMS, user journey orchestration, and SMS platform, so we generate our own data and can change the systems that produce it. That also means analytics here covers both sides of the business. You will report on marketplace performance, and you will measure what product ships: how a change to a user journey affects conversion, whether a new feature did what we expected, and what that tells us to build next. You will be joining shortly after a platform migration, so expect to help define and instrument the events behind that work rather than inherit a mature measurement stack. Over time, we expect this role to grow into quantitative work on how we model and select offers."
We need to keep all that. Could combine into a single
or multiple
. Probably multiple paragraphs okay. Responsibilities: list bullet points after "Responsibilities". Let's extract: - Own marketplace reporting across publishers, advertisers, and verticals, and make sure the numbers the business runs on are correct. - Build and maintain dbt models in the warehouse, with tests, in version control, shipped to production. - Investigate anomalies end to end: what moved, why it moved, and what we should do about it. - Apply LLMs to analytics workflows, including context engineering and evaluation, in partnership with the Analytics Lead. - Measure product work: define success metrics for new features and journey changes, specify the events needed to track them, and report back on whether the change did what we expected. - Partner with operators to define KPIs so the business argues about decisions rather than about whose number is right. - Build self-service reporting so routine questions stop routing through the analytics team. - Own data quality: reconciliation across sources, and validation that catches problems before consumers do. - Support experimentation and measurement design as we roll out platform and product changes. - Grow into quantitative optimization work, including improving how we model and select what offers and experiences we serve to each user session. We need to keep each as
- .
Requirements (Basic Qualifications): list:
- 3 to 5 years of experience in analytics, analytics engineering, or data science.
- Hands-on experience building with LLMs against real data, including how you validated whether the output was trustworthy. Demos and prompt experimentation are not sufficient.
- Production experience with dbt: you have owned models, written tests, worked in Git, and shipped.
- Advanced SQL and working proficiency in Python.
- Experience with a cloud data warehouse (BigQuery preferred, Snowflake or Redshift acceptable).
- Practical experience with data quality work: reconciliation across sources, and validating your own output.
- The ability to hold a business conversation. You should be able to walk us through a question you chased end to end, what you thought was happening, what you found, and what changed as a result.
- Comfort with ambiguity and a track record of deciding what to work on rather than waiting to be told.
Qualifications (Nice to Have / Bonus Qualifications): list:
- Experience in AdTech, performance marketing, or marketplace businesses.
- Experience as the first or only data person at a company.
- Product analytics experience: success metrics, event instrumentation, and measuring feature impact.
- Experimentation design and applied statistics.
- Exposure to bid optimization, yield management, or similar decision-modeling work.
- Familiarity with monitoring and observability tooling such as Datadog or Grafana.
Skills (Moxxi Values & Competencies): list:
- Self-Starter – You take initiative and solve problems before they become problems.
- Curious & Analytical – You ask why, dig deep into data, and experiment to learn what works.
- Efficiency-Oriented – Fast, focused, and action-driven.
- Relationship-Focused – You build trust and deliver value.
- Organized Multitasker – You thrive in fast-paced, high-velocity environments.
- Strategic Communicator – You translate performance into insight and insight into action.
Pay: Salary Range: $120,000 USD - $140,000 USD.
We should not include location as separate heading; could embed in About the role paragraph.
We must not include boilerplate like EEO etc. Not present.
Now produce HTML fragment.
We need to ensure no extra text outside HTML. Provide only HTML.
Let's craft:
About the role
At Moxxi, we’re redefining performance marketing with cutting-edge technology and a relentless focus on results. As a profitable, bootstrapped start-up, we are led by a team of industry veterans in performance marketing, ad tech, and digital publishing. Together, we’re building the premier platform to incubate, scale, and optimize digitally born businesses, setting new standards for data-driven success. Our entrepreneurial team brings proven experience from both global corporations and fast-growing startups. We’re passionate about delivering scalable, profitable outcomes for our partners through advanced profiling, targeting, and continuous optimization. Joining Moxxi means becoming part of a growing start-up in the heart of NYC, where you’ll have the opportunity to accelerate your career, expand your skill set, and shape the future of performance marketing. Location: New York City Level: Mid-level, 3 to 5 years experience
As an Analytics Engineer at Moxxi, you will build and own the data models behind our marketplace reporting, and you will use them to answer questions the business has not yet figured out how to ask. This is a small analytics team, so you will not be handed a queue of tickets. You will work directly with account managers, yield, and product to understand what is actually happening in the business, then build the models and reporting that make those answers repeatable. A significant part of this role is applying LLMs to analytics work: connecting models to the warehouse, engineering the context they need to be useful, and building the evals that tell you whether the output can be trusted. Our Analytics Lead owns this area, and you will be a key contributor to it. Moxxi owns its ad server, CMS, user journey orchestration, and SMS platform, so we generate our own data and can change the systems that produce it. That also means analytics here covers both sides of the business. You will report on marketplace performance, and you will measure what product ships: how a change to a user journey affects conversion, whether a new feature did what we expected, and what that tells us to build next. You will be joining shortly after a platform migration, so expect to help define and instrument the events behind that work rather than inherit a mature measurement stack. Over time, we expect this role to grow into quantitative work on