Data Engineer Jobs

About The Position

Requirements

• 6-10+ years in data engineering/platform roles with significant hands-on delivery.
• Expert SQL and strong Python (or Scala/Java); strong production engineering habits.
• Proven experience designing cloud data pipelines and operating them reliably at scale.
• Experience working with unstructured data processing and search/retrieval concepts.
• Strong communication skills and ability to lead cross-functionally.

Nice To Haves

• Hands-on experience with vector search and embeddings (pgvector/Pinecone/Weaviate/OpenSearch/Elastic) and retrieval patterns (semantic retrieval, hybrid search, reranking).
• Experience supporting LLM applications (RAG, agent tool interfaces, evaluation/observability).
• Knowledge of knowledge graphs/semantic modeling or metrics layers at scale.
• Experience in regulated environments and mature governance programs.

Responsibilities

• Build and own the AI context platform
• Design and implement end-to-end pipelines: ingestion → parsing/chunking → enrichment → embeddings → vector indexing → retrieval/serving.
• Build scalable patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources.
• Improve retrieval quality (query strategies, hybrid search, metadata filtering, reranking hooks) in partnership with AI engineers.
• Deliver semantic and governed data products
• Define and implement semantic layers (metrics/entities) that power BI and agent reasoning consistently.
• Establish data contracts and “context contracts” for AI inputs (schemas, metadata requirements, freshness, citation expectations).
• Ensure datasets and indexes are discoverable, documented, and reusable.
• Operational excellence
• Own reliability and performance: monitoring, alerting, SLAs/SLOs, runbooks, incident response, postmortems.
• Optimize cost and latency across warehouse/lakehouse and vector infrastructure.
• AI safety, governance, and compliance
• Implement security-by-design: RBAC/ABAC patterns, PII redaction, retention controls, audit logging, and safe access pathways for agent tools.
• Partner with Security/Legal/Compliance on guardrails for AI access to enterprise knowledge.
• Lead through influence
• Drive technical direction and roadmap decomposition with product/AI/application stakeholders.
• Set best practices for testing, CI/CD, and evaluation (retrieval eval sets, regression tests, online telemetry).
• Mentor engineers via pairing, code reviews, and lightweight enablement sessions.

Benefits

• medical, dental and vision coverage
• 401(k) plan with a generous employer match
• employee stock purchase plan
• generous Paid Time Off policy
• paid parental leave
• adoption assistance
• Wellness Program supports employee total well-being by providing free annual health screenings and coaching, bank at work, and on-site workshops, as well as ongoing programs recognizing major events in the lives of our employees throughout the year.