Job Details

Senior Product Analytics Engineer

New York, NY

Hybrid Role

$60 - $75 per hour (dependent on years of experience)

ABOUT THE ROLE

Our client, a Fortune Broadcast Media & Entertainment organization, is seeking a Senior Product Analytics Engineer for a 6-month hybrid contract in New York, NY. You will join a 5-person contract team augmenting the Product Analytics & Experimentation organization, working hands-on within a 2-person agile pod. In this role, you will embed into one product workstream at a time, building three foundational analytics tools—a Databricks Metrics View, a Workstream Scorecard, and an AI Analytics Agent—to a defined done bar before rotating to the next workstream. The position emphasizes metrics-as-code, version control, CI/CD, and AI agent benchmarking, focusing on analytics engineering rather than dashboard production. You will report to the Analytics Engineering Manager, partner closely with Data Engineering, and influence Product, Engineering, and Design stakeholders across each workstream. This opportunity offers high-impact work in a collaborative environment, with ownership over deliverables and the chance to influence analytics best practices across multiple product workstreams, powering product decision-making for a major streaming platform.

WHAT YOU'LL DO

• Implement metric, cohort, and segment definitions in the Databricks Metrics View on Unity Catalog using metrics-as-code practices—including PRs, code reviews, and version control.
• Build Workstream Scorecard templates and pipelines that connect goals, drivers, and KPIs with daily/weekly refresh cycles.
• Develop and benchmark the AI Analytics Agent: build eval sets and ground-truth Q&A pairs, run accuracy and regression tests, and manage dev-to-prod promotion through CI/CD workflows.
• Co-own Data Engineering intake within assigned workstreams: identify tagging gaps, validate raw events, document fixes, and track issues to resolution.
• Partner with workstream PMs, engineers, and designers to translate business questions into measurable metrics and agent benchmark cases.
• Document metric logic, cohort definitions, and known data quality issues in a version-controlled environment to support clean handoff to internal analytics teams.
• Collaborate with the Analytics Engineering Manager to harden pod delivery patterns and ensure consistency as the team rotates across workstreams.

WHAT YOU BRING

• 5+ years of experience in product analytics, data analytics, or analytics engineering.
• Advanced SQL skills with experience querying large-scale event or behavioral data.
• Hands-on experience with Databricks and Unity Catalog; familiarity with metrics-as-code tools (e.g., dbt, Cube, MetricFlow).
• Proficiency in Python and Git-based CI/CD workflows, including PRs, code review, automated testing, and dev/prod promotion.
• Experience documenting and benchmarking LLM or agent outputs, including eval sets, ground-truth Q&A pairs, and regression testing.
• Strong fluency in product metrics (engagement states, retention, funnels, cohorts, DAU/WAU/MAU).
• Ability to operate independently within a small pod and rotate cleanly across workstreams.
• Exposure to experimentation/A/B testing (preferred).
• Background in streaming, media, or consumer subscription (preferred).
• Familiarity with Tableau or similar BI tools as a downstream consumer of the metrics layer (preferred).

WHAT'S IN IT FOR YOU

• Hands-on analytics engineering role at a Fortune Broadcast Media & Entertainment organization—building foundational tools that will power product decision-making across a major streaming platform.
• Unique opportunity to work at the intersection of metrics engineering, AI agent benchmarking, and product analytics in an agile, pod-based delivery model.
• Collaborative team environment with real ownership over your workstream deliverables and a clear path from development to production.
• 6-month contract with high-visibility work and meaningful impact on the analytics infrastructure of one of the most recognized streaming platforms in the world.