Staff Data Engineer, Platform Engineering

Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world's health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health.By joining Datavant today, you're stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.What We're Looking ForAs a Staff Data Engineer at Datavant, you will lead the design and build of our next-generation patient data platform, developing the distributed data systems and platform capabilities that power secure, scalable, and intelligent use of data across a multi-tenant, multi-cloud environment.This is a hands-on technical leadership role for a software-oriented data engineer who combines strong architectural judgment with deep implementation expertise. You will define how complex data is processed, validated, and served—supporting analytics, product, and AI-driven use cases in a regulated environment.What You Will DoLead the architecture and development of core data platform capabilities, including processing frameworks, storage patterns, and shared servicesDesign and implement multi-tenant, multi-cloud data systems with strong isolation, scalability, and operational durabilityBuild and operate large-scale distributed data processing systems across batch and real-time workloadsDefine and evolve data lifecycle patterns, including ingestion, validation, transformation, enrichment, and servingEstablish data quality gates and validation frameworks to ensure trust, consistency, and auditabilityDesign systems that integrate with platform infrastructure, including CI/CD, deployment orchestration, observability, and infrastructure automationMake sound architectural decisions across performance, cost, reliability, and maintainability tradeoffsLead ambiguous, high-impact initiatives where both problem definition and solution design require ownershipContribute significantly to production code, setting standards for quality, testing, and operabilityTechnical ExperienceStrong candidates will have experience with several of the following:Distributed data processing frameworks (e.g., Spark, Flink, or similar)Cloud data platforms (e.g., Databricks, Snowflake, or equivalent)Data transformation and modeling frameworks (dbt or equivalent)Workflow orchestration systems (e.g., Airflow or similar)Streaming and event-driven systems (e.g., Kafka or equivalent)Infrastructure-as-code (e.g., Terraform)Modern table formats and lakehouse architectures (e.g., Iceberg, Delta, or similar)What You Need to Succeed10+ years of experience building data-intensive or distributed systems, with a strong software engineering foundationProven experience designing and operating large-scale data platforms in productionDeep 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 debuggingExperience building systems in cloud environments (AWS preferred), including storage, compute, and security patternsExperience designing multi-tenant systems, with a focus on isolation, scalability, and reliabilityStrong understanding of data modeling, pipeline design, and data quality enforcementAbility to navigate ambiguity, evaluate tradeoffs, and drive durable technical decisionsTrack record of being a high-impact, hands-on contributor who leads through both design and executionWhat Helps You Stand OutExperience building data systems that support AI-driven use cases, including:low-latency data access patternsfeature generation and ML data pipelinesiterative, feedback-driven data workflowsFamiliarity with agentic or AI-assisted coding tools, and the ability to leverage them to improve development velocity and code qualityComfort operating in environments where AI augments both system design and development workflowsExperience 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 transformationsThe range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job.The estimated total cash compensation range for this role is:$190,000—$230,000 USDThis job is not eligible for employment sponsorship.We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.J-18808-Ljbffr