Description

Build serving stores, sync pipelines, and API layers for AI pilot use cases, configuring end-to-end integrations and maintaining SLAs for latency, freshness, and availability.

This role is on-site.

Responsibilities

• Configure pilot end-to-end setups including source table binding, key schema, sync schedules, and consumer integration.
• Establish CI/CD pipelines with automated tests for sync correctness, API contract validation, and latency benchmarks.
• Operate data products to defined SLAs for latency, freshness, and availability.
• Partner with domain teams to onboard use cases onto established patterns and contribute to reference implementations and documentation.

Required Skills

• Production Python with FastAPI or comparable frameworks for versioned REST APIs.
• Experience with Kafka or comparable streaming platforms and CDC or incremental batch pipelines.
• Hands-on production experience with Redis or Valkey for caching, key-value serving, and cache invalidation.
• Proficiency with vector databases or knowledge graphs such as Pinecone, Weaviate, pgvector, or Neo4j.
• Production experience with Azure Databricks, Delta Lake, and Unity Catalog, including Delta Lake internals.
• Strong SQL skills and understanding of data modeling for point-lookup versus analytical queries.
• CI/CD tooling experience with GitLab or GitHub Actions.

Preferred Skills

• Experience with embedded analytical engines like DuckDB.
• Production experience with Microsoft Fabric, OneLake, or Power BI Semantic Models.

Key Skills

Education

Bachelor's degree