Senior Analytics Engineer, AI & DX Analytics

Role overview A Senior Analytics Engineer is needed on a team that measures and improves developer experience and AI investment across a large engineering organization. The role sits at the intersection of raw engineering signals (AI coding agent sessions, pull request and CI activity, AI tooling spend) and the executive reporting that drives AI investment decisions. The work covers the full pipeline: instrumenting new telemetry at the source, landing it in governed tables, defining fresh metrics, and packaging them into dashboards and visual narratives for senior leadership.

Responsibilities - Design and extend telemetry that captures AI usage, code changes, CI/CD activity, and AI tooling spend, building new event capture rather than only reshaping what already exists. - Partner with data engineers on production ETL pipelines with freshness monitoring, backfills, and alerting so the underlying data stays trustworthy. - Define new metrics from ambiguous or evolving signals, then validate and reconcile them until stakeholders trust the number. - Build executive-facing dashboards and visualizations that turn governed metrics into decision-ready reporting, with the polish needed for a leadership audience. - Run the analysis behind new charts, anticipate executive questions, and deliver recommendations backed by defensible methodology. - Use AI coding agents as a default part of writing, testing, and maintaining pipelines, dashboards, and analyses. - Collaborate with data engineering, applied AI, and data science teams so raw telemetry flows end to end into session classifiers as well as dashboards. - Translate findings into concrete actions, flagging where AI spend underperforms or where developer friction is most costly.

Requirements - 8+ years in analytics engineering, data engineering, or business intelligence, with end-to-end ownership of production pipelines and insights. - Background in developer experience, engineering productivity, measuring AI effectiveness, or platform analytics. - Strong SQL and Python, with hands-on experience building and operating pipelines against a cloud data warehouse such as Snowflake. - Experience partnering with engineering teams to define and instrument new event or telemetry data, not just transform existing datasets. - Track record building dashboards or internal tools that non-technical stakeholders rely on for decisions, with sound judgment on when something is decision-ready. - Comfort owning a dashboard's data layer and performance, including profiling slow queries, adjusting caching or prequery logic, and shipping frontend changes in a framework like React. - Proficiency with git, CI/CD systems, and debugging production pipeline failures such as retries and backfills. - Daily workflow built around AI coding agents as a primary tool. - Strong written and verbal communication, including experience presenting to senior audiences.

Nice to have - Familiarity with data modeling for fast-changing AI tooling telemetry and willingness to define metrics that do not yet have industry-standard definitions.

Benefits and work setup - Remote work options, medical insurance, flexible time off, retirement savings plans, and modern family planning benefits. - Market-based pay with U.S. zones ranging from approximately $139,000 to $245,400 USD depending on location, skills, and experience.