Note: The job is a remote job and is open to candidates in USA. Komodo Health is hiring a Senior Data Platform Engineer to build, operate, and improve the large-scale data pipelines and foundational platform behind its Healthcare Map. The role focuses on processing complex healthcare data at scale, improving reliability and performance, and contributing to the technical direction of core data systems.

Responsibilities

• Build, operate, and optimize large-scale batch pipelines using Python, SQL, Spark, and Airflow on AWS
• Make storage and data layout decisions (table formats, partitioning, file sizing, compaction) that keep large datasets fast to query and cost-efficient
• Ingest data from many external sources and keep pipelines correct through frequent schema changes
• Transform healthcare claims, EHR, and reference data into trusted, serving-ready data products for customers and internal teams
• Strengthen reliability through data quality checks, validation, lineage, observability, and alerting
• Debug complex data, system, and performance issues across compute-heavy workflows
• Contribute to system design, code quality, testing, documentation, CI/CD, and rotational production support

Skills

• Strong hands-on experience building, owning, and debugging production data pipelines at multi-terabyte scale
• Advanced Python, including performant, memory-efficient code for large-scale data processing, plus strong SQL
• Deep production experience with Airflow, including operating and scaling it, not just writing DAGs
• A solid understanding of how data is physically stored: columnar vs. row formats, and open table formats like Iceberg, Delta Lake, or Hudi (updates, compaction, small files, partitioning)
• Experience with Spark or a comparable distributed processing framework
• Proven experience designing and operating data systems in AWS
• Strong instincts for data correctness, root-cause analysis, and production troubleshooting
• The ability to communicate technical trade-offs clearly with engineering, product, and data partners
• Comfort using AI-assisted engineering tools for coding, debugging, documentation, and technical exploration
• Containers and orchestration (Docker, Kubernetes)
• Strong core software engineering fundamentals and experience in more than one language
• Data governance and lineage experience
• Experience delivering external-facing data products through APIs, serving layers, or customer access patterns
• Experience applying AI or agentic workflows to engineering, data quality, delivery, or operations
• Success in high-growth or ambiguous environments

Benefits

• Performance-based bonuses, as determined in the Company's sole discretion and in accordance with a written agreement or plan
• May be eligible for equity awards
• Comprehensive health, dental, and vision insurance
• Flexible time off and holidays
• 401(k) with company match
• Disability insurance and life insurance
• Leaves of absence in accordance with applicable state and local laws and regulations and company policy
• Open to US remote, OR SF/NYC hybrid

Company Overview

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