Sr. Forward Deployed Data Engineer

Role overview Serve as a senior hands-on engineer who turns business teams’ data and AI needs into production analytics products and workflows. The role combines stakeholder discovery and technical advising with building pipelines, governed data models, semantic layers, and LLM-powered automation. Solutions must fit shared platform standards and meet rigorous quality, privacy, and governance expectations for sensitive clinical and genomic information.

Responsibilities - Work directly with business partners to understand needs, assess the impact of new products or assays, and shape technical plans and milestones. - Build and operate scalable data pipelines and transformations that bring together clinical, laboratory, operational, and commercial data. - Create governed models and semantic layers for self-service analytics, dashboards, and data products. - Develop AI workflows using retrieval, agents, and LLM pipelines for tasks such as extraction and classification. - Implement data quality checks, contracts, lineage, monitoring, and durable fixes for complex data issues; own service reliability and cost efficiency. - Apply access controls, auditability, retention, and other safeguards for regulated data, while collaborating with platform and AI teams and communicating tradeoffs clearly.

Requirements - At least seven years in data or software engineering, including delivery of analytics or AI solutions directly with stakeholders in forward-deployed or customer-facing work. - Strong stakeholder communication and project delivery skills, including the ability to explain technical concepts to non-technical partners. - Expert SQL and strong Python, with experience shipping and operating production pipelines and data models at scale. - Practical experience with cloud data warehouses and infrastructure; Snowflake and AWS are preferred. - Hands-on knowledge of dbt or an equivalent transformation framework, plus an orchestrator such as Airflow, Dagster, or Prefect. - Daily experience with AI coding assistants and agentic tools, plus 1–2 years building with LLM frameworks and managed AI services. - Strong grounding in analytical modeling, semantic layers, data quality, and CI/CD for data systems.

Nice to have - Experience in healthcare, life sciences, or another regulated field.

Benefits and work setup - Employee benefits include medical, dental, vision, life, and disability coverage for eligible employees and dependents; family testing and fertility care benefits; bonding leave; retirement savings; and commuter benefits.