Sr Manager IC, FinOps & AI Enablement

• Analytics Team (Remote
• Eligible) The role Own the cost and AI-leverage layer of the analytics platform behind Capital One Shopping
• the systems between petabyte-scale data and the humans and tools that query it.

This is an own-and-build role, not a maintenance seat: you own the production platforms below, and in your first six months you ship three net-new systems on top of them. You'll report to the Engineering Director for the Shopping data platform as one of two senior IC pillars of the analytics org. What you own You own, support, and evolve three production platforms

• ideation through implementation to production support
• and you're the SME and mentor for the analysts, BAs, and engineers who use them: + A data warehousing platform serving ~250K queries/day over ~20PB. + An event ingestion pipeline taking in 6-7 billion events/day. + The Airflow orchestration platform. You own the technology choices and the strategic backlog and priorities for this surface
• and you carry ongoing production support and an on-call rotation for these platforms and the models on them. You build the three net-new systems below on top of that operational base. What you'll build + A cost-attribution pipeline that parses Trino query logs at production traffic and attributes real AWS dollars to every report, query, user, and dbt model
• reconciled against a ~$750K/month cloud bill. + A forecast-driven autoscaling control loop for the shared Trino cluster and dbt worker pool
• turning today's event-only Nomad autoscaler (Prime Day, Cyber Week) into steady-state, forecast-driven capacity. The single largest lever on the analytics AWS bill. + A production Gen AI system
• natural-language-to
• SQL or RAG over the data catalog
• with real LLM tool-use, grounding, and cost guardrails, adopted by internal teams.

The stack Kafka streaming backbone into an S3 lakehouse (Hive + Iceberg), Cassandra, Postgres, DynamoDB, ElasticSearch, Aurora MySQL. Queried through Trino/Presto and Spark SQL , modeled in dbt, orchestrated on Airflow and Nomad and containers (Docker/Kubernetes), on a deep AWS footprint. SQL and Python daily; Go, Java, and TypeScript/JavaScript across the surrounding platform. The day-to-day "Manager" is the level, not the job

• this is an individual-contributor role, and you'll spend most of your day hands-on in the editor.

Roughly 70% building: writing the log-parsing and cost-attribution logic a To view full details and how to apply, please login or create a Job Seeker account