Tech Lead, Data & Inference Engineer

Primer is seeking a Tech Lead, Data & Inference Engineer to own the design, delivery, and scaling of our end-to-end data platform. You’ll oversee the full lifecycle from ingestion to insights, turning diverse sources into trusted, low-latency data that helps Primer move fast and make better decisions. This role is pivotal for spreading data-driven thinking across teams and elevating data quality, reliability, and impact.

What youll do

• Design and ship scalable batch and streaming data pipelines, prototype and optimize critical paths, and mentor the team.
• Own reliability, cost, and SLOs by instrumenting observability and capacity, targeting ≥99.9% uptime and minutes-level latency.
• Operate pragmatic inference pipelines (enrichment, scoring, QA with LLMs/RAG) with versioning, canarying, caching, and evaluation loops.
• Partner cross-functionally to treat data as a product—define audiences and contracts, manage lifecycle, and validate impact through usage.
• Drive data lake and pipeline architecture, document trade-offs and lineage, and articulate build-vs-buy decisions.
• Scale integrations with third-party APIs and internal services, resolve data conflicts, and support both sub-second queries and large batch workflows.

What Primer is looking for

• 6+ years in Data Engineering roles.
• Very strong Node.js skills; proficient in Python and SQL.
• Experience with distributed data systems (Spark, Flink, Kafka) and orchestration tools (Airflow, Dagster, Prefect).
• Experience with dbt, DuckDB, and the modern data stack.
• Familiarity with IaC, CI/CD, and observability fundamentals.
• Experience optimizing SQL queries on large datasets.
• Previous early-stage experience at a high-growth startup (10-200 people).
• Open to collaborating in person in downtown SF 4-5 days a week.
• Experience leading projects and building products.
• Strong CS fundamentals.