Datavant is the data collaboration platform trusted for healthcare, focusing on making health data secure, accessible, and actionable. The Senior Data Engineer will lead the design of scalable data platform infrastructure and collaborate with various stakeholders to translate business needs into technical solutions.
Responsibilities:
- Lead the design and evolution of scalable data platform infrastructure, orchestration frameworks, and modeling patterns that support reporting, analytics, operational systems, and new business domains
- Drive complex, cross-functional initiatives with broad scope, balancing technical tradeoffs between scalability, reliability, maintainability, cost efficiency, and speed of delivery
- Mentor and guide engineers across the team, helping establish best practices for data modeling, orchestration, observability, Infrastructure-as-Code, and operational excellence
- Facilitate technical discussions and architecture decisions, acting as a trusted technical leader and escalation point for complex engineering challenges
- Partner closely with stakeholders across Product, Engineering, Analytics, and Operations to translate ambiguous business needs into scalable technical solutions and platform capabilities
- Design and maintain reliable, observable, and reusable data workflows using Python, SQL, dbt, Airflow, Terraform, and cloud-native technologies
- Establish and evolve standards for testing, monitoring, incident response, operational reliability, security, and cost optimization across the platform
- Review and guide code, infrastructure, and architectural decisions to ensure high standards for quality, extensibility, maintainability, and operational excellence
Requirements:
- 7+ years of progressive experience in software development or data engineering, with demonstrated leadership in complex technical initiatives and cross-functional collaboration
- AI-first mindset with hands-on experience leveraging AI-assisted engineering tools such as Claude Code, Cursor, GitHub Copilot, and ChatGPT to improve developer productivity, operational efficiency, code quality, and scalability
- Deep expertise in modern data modeling and transformation practices, including scalable and maintainable architecture patterns across analytical and operational domains
- Strong experience designing reusable pipeline frameworks and orchestration strategies using dbt, Apache Airflow, Python, and cloud-native technologies
- Strong experience designing and operating cloud-based data platforms in AWS, Azure, or GCP, including Infrastructure-as-Code using Terraform or comparable frameworks
- Experience leading platform reliability initiatives including observability, monitoring, incident response, operational excellence, performance optimization, and cost management
- Strong familiarity with CI/CD pipelines, GitOps workflows, automated testing strategies, and modern software engineering best practices for scalable and reliable data platforms
- Strong technical leadership and communication skills, including mentoring engineers, influencing technical direction, and aligning cross-functional stakeholders
- Ability to lead through ambiguity, balance competing priorities, and drive high-impact initiatives from concept through delivery
- Prior experience in healthcare or another highly regulated industry such as finance, insurance, or life sciences
- Experience administering and optimizing Snowflake or similar cloud data warehouse platforms, including security and access management, performance tuning, workload management, cost optimization, governance, and operational reliability at scale
- Hands-on experience with modern data stack technologies such as dbt, Fivetran Airflow, Kafka, Spark, Databricks, or streaming/event-driven architectures
- Strong understanding of data governance, privacy, lineage, and compliance frameworks such as HIPAA, HITRUST, SOC2, or GDPR
- Background as a Database Administrator, Data Analyst, Analytics Engineer, or similar data-focused role
- Experience building self-service data platforms, reusable developer tooling, or internal platform capabilities that improve engineering productivity
- Experience supporting multi-cloud or hybrid-cloud infrastructure and networking patterns across AWS and/or Azure