Senior Data Platform Engineer
The Opportunity at Komodo Health
Join Komodo Health’s Data Foundations team and play a critical role in shaping the core data products that fuel our Healthcare Map. You’ll transform massive, complex healthcare datasets into performant, trustworthy data assets that power customer-facing products, internal innovation, and AI/ML use cases. By building and scaling our foundational data systems, you’ll directly enable the transparency and efficiency required to drive better health outcomes across the industry.
Mission
The Senior Data Platform Engineer will design, build, operate, and improve the large-scale pipelines and foundational data platform behind Komodo’s Healthcare Map. This is a hands-on engineering role focused on processing complex healthcare data at scale, improving reliability and performance, and contributing to the technical direction of core data systems.
Looking back on your first 12 months at Komodo Health, you will have…
Architectural Advancement: Delivered high-impact technical initiatives that improve pipeline performance, scalability, and system efficiency.
Platform Hardening: Improved the reliability, observability, and cost-efficiency of core Data Foundations systems.
Healthcare Data Innovation: Built deep domain expertise and contributed new approaches to challenges such as patient journey mapping and identity resolution.
Cross-Functional Delivery: Partnered with Data Product and Engineering teams to ship scalable, production-grade data solutions.
Architecture Partnership: Raised the bar across the team through mentorship, design reviews, and engineering best practices.
Key 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
What you bring to Komodo Health:
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
AI-Augmented Engineering Expectations:
You will be expected to leverage AI-augmented engineering tools, such as ChatGPT, Gemini, or Claude, to improve productivity and technical decision-making. This may include using AI to generate and refine code, accelerate documentation, automate test case creation, debug complex issues, explore unfamiliar technical concepts, and assess architectural trade-offs and risks.
Additional skills and experience we’d prioritize (nice to have)…
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
No healthcare background required. You’ll build that domain expertise here.
**Open to US remote, OR SF/NYC hybrid
#LIRemote
The pay range for each job posting reflects a minimum and maximum range of annual base pay that we reasonably expect to pay for this position within the US. We carefully consider multiple business-related factors when determining compensation, including job-related skills, work experience, geographic work location, relevant training and certifications, business needs and market demands.
The starting annual base pay for this role is listed below. This position may be eligible for performance-based bonuses as determined in the Company’s sole discretion and in accordance with a written agreement or plan. This role may also be eligible for equity awards. In addition, this role is eligible for benefits including, but not limited to, comprehensive health, dental, and vision insurance; flexible time off and holidays; 401(k) with company match; disability insurance and life insurance; and leaves of absence in accordance with applicable state and local laws and regulations and company policy.
San Francisco Bay Area and New York City:
$196,000—$230,000 USD
All Other US Locations:
$170,000—$200,000 USD