Analytics Engineer

Build trusted marketplace analytics for Moxxi Digital’s performance and product decisions while applying modern data engineering workflows and LLMs to analytics. This onsite role in New York, NY offers the chance to own reporting end to end, strengthen data quality, and help teams measure what changes actually do.

Salary: USD 120,000 - 140,000 per year. Experience: 3 to 5 years.

What you’ll do

• Own marketplace reporting across publishers, advertisers, and verticals, ensuring the numbers the business relies on are accurate.
• Build and maintain dbt models in the warehouse, adding tests, working in version control, and shipping to production.
• Investigate anomalies end to end: determine what changed, why it changed, and what actions should follow.
• Apply LLMs to analytics workflows, including context engineering and evaluation, in partnership with the Analytics Lead.
• Measure product work by defining success metrics for new features and journey changes, specifying required events, and reporting whether outcomes match expectations.
• Partner with operators to define KPIs so discussions focus on decisions rather than whose number is correct.
• Build self-service reporting so recurring questions don’t need to route through the analytics team.
• Own data quality through reconciliation across sources and validation that prevents issues before downstream consumers see them.
• Support experimentation and measurement design as the platform and product evolve.
• Grow into quantitative optimization, improving how offers and experiences are modeled and selected for each user session.

What you bring

• 3 to 5 years of experience in analytics, analytics engineering, or data science.
• Hands-on LLM experience with real data, including how you validated trustworthiness. (Demos and prompt experiments alone are not enough.)
• Production dbt experience: ownership of models, writing tests, using Git, and shipping changes.
• Advanced SQL and working proficiency in Python.
• Cloud warehouse experience (BigQuery preferred; Snowflake or Redshift acceptable).
• Practical data quality experience, including reconciliation across sources and validation of your own output.
• Ability to hold a business conversation, including walking through a question you chased from start to finish, what you inferred, what you found, and what changed as a result.
• Comfort with ambiguity and a track record of choosing what to work on rather than waiting for direction.

Nice to have

• Experience in AdTech, performance marketing, or marketplace businesses.
• Experience as the first or only data person at a company.
• Product analytics experience, including 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 tools such as Datadog or Grafana.

Values & competencies

• Self-Starter – take initiative and solve problems before they become problems.
• Curious & Analytical – ask why, dig deep into data, and experiment to learn what works.
• Efficiency-Oriented – fast, focused, and action-driven.
• Relationship-Focused – build trust and deliver value.
• Organized Multitasker – thrive in fast-paced, high-velocity environments.
• Strategic Communicator – translate performance into insight and insight into action.

Technologies

dbt, SQL, Python, BigQuery, Snowflake, Redshift, Git, LLMs