Lead Data Engineer - Healthcare Data & Audience Applications

Role overview Lead the architecture and hands-on delivery of data systems and applications for healthcare audience discovery, activation, measurement, and reporting. The work spans provider and patient workflows, identity resolution, data pipelines, and partner integrations, with privacy, compliance, and dependable operations built into the design. You’ll provide technical direction while contributing directly to implementation.

Responsibilities - Define healthcare data architecture, schemas, interface contracts, decision records, and staged delivery plans. - Lead ingestion and transformation across data platforms and approved healthcare stores, coordinating source certification, partner feed agreements, identity validation, and data availability expectations. - Design governed healthcare models and views with appropriate account scoping, row or member controls, masking, and backward-compatible changes. - Establish service objectives and release readiness, including dashboards, alerts, runbooks, rollback plans, and incident ownership. - Lead design and code reviews, mentor a senior engineer, and coordinate dependencies across the team. - Support audits, compliance evidence, data residency controls, and privacy-by-design practices for systems handling sensitive health and personal data.

Requirements - At least eight years of data engineering experience with increasing technical ownership. - Expert SQL skills and strong Python and Java, with experience in batch and streaming workloads, orchestration, testing, and schema evolution. - A track record of designing and scaling data-intensive or distributed systems, including strong architecture and system design skills. - Experience in regulated environments and a solid understanding of healthcare privacy and data handling requirements. - Ability to lead technical work while remaining hands-on, and to collaborate across engineering, product, and data teams. - Familiarity with data quality, lineage, access controls, masking, retention, auditability, observability, and cost management.

Nice to have - Experience with provider or patient data, healthcare data ecosystems, identity graphs, or healthcare data providers. - Background in audience, advertising, or marketing data platforms; familiarity with tokenization, clean rooms, or analytics and machine learning products.

Benefits and work setup The listed benefits include flexible paid time off, medical, dental, and vision coverage, employee equity, discounts, wellness classes, and pet insurance.