Senior Data Platform Engineer
Skills
- Hands-on experience with Databricks and modern lakehouse/warehouse architectures
- Proven ability building and supporting production-scale ETL/data pipelines
- Familiarity with cloud infrastructure (AWS preferred) and cost optimization strategies
- Experience with access control, data governance, and security for data platforms
- Strong reliability, observability, and monitoring practices for infrastructure
- Excellent communication and stakeholder collaboration skills
Responsibilities
- Collaborate with engineering, data science, ML, data engineering, and analytics teams to define platform requirements and roadmaps
- Design and implement live data ingestion layers (e.g., Kafka, Kinesis) and scalable pipeline patterns
- Define and enforce standards for storage, compute, data management, provenance, and orchestration
- Build reusable tooling and frameworks for data quality monitoring, templated pipelines, and backfill capabilities
- Implement and manage role-based access control, data governance, and security practices
- Monitor and forecast infrastructure usage and costs; optimize for performance and cost-efficiency
- Ensure reliability, observability, and monitoring for data infrastructure and pipelines
Education
- Bachelor's degree in Computer Science or a related engineering field
- Master's degree preferred (Computer Science, Data Engineering or similar)
Benefits
- Competitive salary plus equity
- Medical, dental, and vision insurance
- Flexible PTO
- Remote-first role (US & Canada)
- Opportunities to work cross-functionally with clinicians, data scientists, and product teams
Average salary estimate
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