Staff Data Engineer, Platform Engineering

Datavant is the data collaboration platform trusted for healthcare, dedicated to making the world's health data secure, accessible, and actionable. As a Staff Data Engineer, you will lead the design and build of a next-generation patient data platform, focusing on developing distributed data systems and platform capabilities that support secure and intelligent data use across a multi-tenant, multi-cloud environment.

Responsibilities:

• Lead the architecture and development of core data platform capabilities, including processing frameworks, storage patterns, and shared services
• Design and implement multi-tenant, multi-cloud data systems with strong isolation, scalability, and operational durability
• Build and operate large-scale distributed data processing systems across batch and real-time workloads
• Define and evolve data lifecycle patterns, including ingestion, validation, transformation, enrichment, and serving
• Establish data quality gates and validation frameworks to ensure trust, consistency, and auditability
• Design systems that integrate with platform infrastructure, including CI/CD, deployment orchestration, observability, and infrastructure automation
• Make sound architectural decisions across performance, cost, reliability, and maintainability tradeoffs
• Lead ambiguous, high-impact initiatives where both problem definition and solution design require ownership
• Contribute significantly to production code, setting standards for quality, testing, and operability

Requirements:

• 10+ years of experience building data-intensive or distributed systems, with a strong software engineering foundation
• Proven experience designing and operating large-scale data platforms in production
• Deep expertise in distributed data processing systems (e.g., Spark or similar big data technologies)
• Strong software engineering fundamentals, including system design, testing, CI/CD, and production debugging
• Experience building systems in cloud environments (AWS preferred), including storage, compute, and security patterns
• Experience designing multi-tenant systems, with a focus on isolation, scalability, and reliability
• Strong understanding of data modeling, pipeline design, and data quality enforcement
• Ability to navigate ambiguity, evaluate tradeoffs, and drive durable technical decisions
• Track record of being a high-impact, hands-on contributor who leads through both design and execution
• Experience building data systems that support AI-driven use cases, including low-latency data access patterns, feature generation and ML data pipelines, iterative, feedback-driven data workflows
• Familiarity with agentic or AI-assisted coding tools, and the ability to leverage them to improve development velocity and code quality
• Comfort operating in environments where AI augments both system design and development workflows
• Experience in regulated environments (e.g., healthcare, finance)
• Familiarity with interoperability standards (e.g., FHIR, HL7, or similar)
• Experience leading large-scale platform migrations or architectural transformations