Director, Data and Platform

Role overview A small, high-leverage AI engineering team is hiring a Director of Data and Platform Architecture to own the full data lifecycle, from ingestion through ETL, transformation, extracts, and stakeholder dashboards. The role also owns DevOps and infrastructure for the AI engineering team, with the expectation that the director stays hands-on and writes production code while leading and growing the team.

Responsibilities - Own end-to-end data architecture, including ingestion, ETL and transformation, extracts, and the reporting layer that feeds downstream dashboards. - Set technical direction for data infrastructure, pipelines, platform reliability, and engineering standards. - Design and build the AI engineering platform from ingestion through serving, taking it to production-grade quality with proper observability. - Write, review, and ship production code as part of the team's day-to-day output. - Hire, develop, and lead engineers, mentoring them on architecture, data design, DevOps, and platform thinking. - Translate business and executive priorities into a data and platform strategy that maps investments to outcomes.

Requirements - Eight or more years architecting and building production platforms, with a record of hands-on delivery rather than purely design work. - Direct experience owning data architecture across ingestion, ETL, transformation, extracts, and BI/reporting layers. - Deep, hands-on DevOps background including GitOps workflows, Kubernetes, and cloud infrastructure such as AWS. - Proficiency across the modern data stack: distributed processing like Spark or Kafka, NoSQL stores such as MongoDB or DynamoDB, warehouses like Snowflake, Redshift, or BigQuery, and transactional systems such as Postgres or MySQL, with rigorous PHI/PII handling. - Strong communication and collaboration skills, with the ability to explain architecture tradeoffs to engineers, peers, and executives. - Prior experience mentoring engineers and either leading a team or clear readiness to take on direct reports. - Comfort operating in a small, fast-moving environment where the role wears multiple hats.

Nice to have - Experience architecting data platforms that support AI or ML workloads. - Familiarity with vector databases for AI/ML retrieval such as Qdrant, Pinecone, or Weaviate. - Background in healthcare, pharmacy benefits, or other regulated data environments. - Experience standing up greenfield data platforms from scratch rather than only extending existing systems.

Benefits and work setup The posted salary range is 220,000 to 260,000. Additional compensation details were not specified in the source material.