Senior Analytics Engineer, AI & DX Analytics

What you'll do

• Instrument AI usage, code changes, CI/CD activity, and spend telemetry; partner on production pipelines, monitoring, backfills, and alerting.
• Define and validate metrics, build executive-facing dashboards, and communicate findings with recommendations to senior stakeholders.
• Use AI coding agents and collaborate across teams to assess AI ROI and quantify AI- and agent-related productivity impact.

What they ask for

• Strong SQL and Python, with hands-on experience building and operating data pipelines against a cloud data warehouse such as Snowflake.
• Experience instrumenting event or telemetry data with engineering teams, and building dashboards or internal tools used by non-technical decision-makers.
• Comfort with git, CI/CD systems, and debugging production pipeline failures, including retries and backfills.
• Self-sufficient across instrumentation, pipeline building, metric definition, and dashboards; able to communicate and defend methodology to senior stakeholders.

Nice to have

• Experience with a metrics-governance or semantic-layer system, such as a metrics store, dbt semantic layer, or LookML.

Pay

$163,600 — $245,400 USD (base salary); $155,400 — $233,200 USD (base salary); $146,900 — $220,300 USD (base salary); $139,000 — $208,600 USD (base salary)

Tools

SQL (Snowflake), Python, TypeScript and React, Git, CI/CD pipelines, a governed metrics store, AI coding agents, LLM-based classification tooling

AI focus

Measure AI investment and ROI, improve developer experience, and develop metrics for the productivity impact of AI- and agent-augmented engineering. AI coding agents are a default tool for building and maintaining pipelines, dashboards, and analyses.