Lead Data Engineer - Healthcare Data & Audience Applications

Overview

Lead a hands-on technical leadership role building and scaling healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across HCP and DTC workflows.

What you'll do

• Build applications supporting HCP and patient / direct-to-consumer (DTC) audience discovery, segmentation, and activation
• Build scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
• Build identity resolution and data linkage services across fragmented data sources
• Build reporting, attribution, and measurement systems connecting campaigns to outcomes
• Build APIs and services enabling downstream activation, analytics, and partner integrations
• Define and maintain the healthcare data architecture, interface contracts, ADRs, schemas, and staged delivery plan
• Lead ingestion and transformation patterns across Snowflake, Athena/S3, MySQL, and approved healthcare stores
• Partner with Data Cloud on source certification, partner-feed contracts, identity validation, raw-zone ownership, and data availability SLAs
• Design healthcare base/vertical models and published/governed views, with row/member-level controls, account scoping, masking, and backward-compatible versioning
• Set SLOs and operational readiness criteria; ensure dashboards, alerts, runbooks, rollback paths, and incident ownership are in place before release
• Lead design and code reviews, mentor the Senior Data Engineer, and coordinate dependencies across the pod
• Support compliance evidence, annual audits, US data-residency controls, and stoplight decisions (Start, Stop, or Requires CERT)
• Apply privacy-by-design principles across all systems handling PHI/PII
• Partner with Product and Data teams to translate healthcare requirements into scalable architectures
• Drive engineering best practices across testing, CI/CD, code quality, and operational excellence

What you'll need

• 8+ years of data engineering experience with increasing technical ownership
• Expert SQL and strong Python and Java; experience with batch and streaming patterns, orchestration, testing, and schema evolution
• Strong experience designing distributed systems, including microservices and event-driven architectures
• Deep understanding of data modeling, storage systems (OLTP and OLAP), and data-processing frameworks
• Experience with streaming and batch processing technologies such as Kafka, Spark, Flink, or similar tools
• Proficiency in backend development using Python, Java, or Ruby, and API design using REST or gRPC
• Experience with workflow orchestration tools such as Apache Airflow
• Experience working with data warehouses and lakehouse platforms such as Snowflake, Databricks, or similar technologies
• Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code
• Familiarity with containerization and orchestration technologies, including Docker and Kubernetes
• Experience implementing observability practices, including logging, metrics, and tracing, as well as reliability patterns
• Strong understanding of performance optimization and scalability trade-offs
• Experience working with HCP data (provider identity, targeting, segmentation)
• Experience with patient / DTC data workflows and privacy-aware systems
• Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
• Familiarity with identity graphs and data onboarding patterns
• Experience building reporting or attribution systems tied to business outcomes
• Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements
• Proven track record of building and scaling data-intensive or distributed systems
• Experience working in regulated environments
• Strong system design and architecture skills
• Ability to lead technically while remaining hands-on in implementation
• Strong collaboration skills across engineering, product, and data teams

Nice to have

• Experience with healthcare data providers or identity ecosystems
• Background in AdTech, MarTech, or audience/data platforms
• Experience with privacy-enhancing technologies (tokenization, clean rooms)
• Exposure to ML/AI-driven data products or analytics systems

Details

• Remote, United States
• Salary range $180,000 - $200,000, depending on location and experience