Lead Software Engineer - Healthcare Data & Audience Applications

What you'll do

• Lead architecture and hands-on development of distributed systems supporting healthcare data workflows
• Design and implement scalable data pipelines (batch and streaming) for large-scale datasets
• Build and maintain APIs and services with strong SLAs, observability, and fault tolerance
• Implement identity resolution logic including matching, deduplication, and graph-based linkage
• Ensure high data quality through validation, reconciliation, and monitoring frameworks
• Design systems with strong security controls, including encryption, access control, and auditability
• 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
• Mentor engineers and act as a technical leader across the team

Requirements

• 8–10 years of software engineering experience with increasing technical ownership
• Proven track record of building and scaling data-intensive or distributed systems
• Experience working in regulated environments (healthcare strongly preferred)
• 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
• Experience designing distributed systems (microservices, event-driven architectures)
• Deep understanding of data modeling, storage systems (OLTP, OLAP), and data processing frameworks
• Experience with streaming and batch processing (e.g., Kafka, Spark, Flink, or similar)
• Proficiency in backend development (Python, Java, or Ruby) and API design (REST/gRPC)
• Experience building modern front-end applications (React or similar)
• Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
• Familiarity with containerization and orchestration (Docker, Kubernetes)
• Experience implementing observability (logging, metrics, tracing) and reliability patterns
• Strong understanding of performance optimization and scalability tradeoffs
• 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

Tech stack

Benefits