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Senior Data Platform Engineer

Join Komodo Health as a Senior Data Platform Engineer to shape core data products that drive better health outcomes.

Location
San Francisco, CA, United States
Compensation
$196k–$230k/yr
Level
senior
Type
full time · Hybrid

Posted by employer 2 days ago

First seen on Joblaze 1 day ago

Last verified on the company career page 1 day ago

Apply at Komodo Health → Save job Scanned from komodohealth.com

Skills & Technologies

What you'll build

  • Build, operate, and optimize large-scale batch pipelines
  • Make storage and data layout decisions
  • Ingest data from many external sources
  • Transform healthcare claims, EHR, and reference data
  • Strengthen reliability through data quality checks

Must have

  • Strong hands-on experience building production data pipelines
  • Advanced Python skills
  • Deep production experience with Airflow
  • Understanding of data storage formats
  • Experience with Spark or distributed processing frameworks
  • Proven experience designing data systems in AWS

Nice to have

  • Containers and orchestration experience
  • Strong core software engineering fundamentals
  • Data governance and lineage experience
  • Experience delivering data products through APIs
  • Experience applying AI to engineering workflows

Role intensity

70% hands-on coding

AI in the day-to-day

You will be expected to leverage AI-augmented engineering tools to improve productivity and technical decision-making.

Not disclosed in this posting: years of experience, visa sponsorship.

Benefits

401k Match Unlimited PTO Equity/Stock Options Health Insurance

Joblaze summary

The Senior Data Platform Engineer at Komodo Health focuses on designing and optimizing large-scale data pipelines that transform complex healthcare datasets into reliable data products. Proficiency in Python, SQL, Spark, and Airflow is essential, alongside experience in AWS and data storage strategies. This role is suited for experienced engineers who can navigate multi-terabyte data environments and communicate effectively with cross-functional teams. Komodo Health emphasizes a collaborative culture, where team members are encouraged to leverage AI tools to enhance productivity and decision-making.

Joblaze insights

  • Listed yesterday — first seen on Joblaze October 25, 2026. Last confirmed on Komodo Health's careers page October 25, 2026.
  • This exact title is also open at 1 other location at Komodo Health: New York, New York.
  • Salary band is in line with the typical range for Data Engineering roles (median ~$180,656).
  • Starts above 91% of 132 comparable senior data engineering roles in United States that list Python we track (median $180,656 across 35 companies). See Python salary trends
  • Python appears in 77.6% of 214 comparable senior data engineering roles in United States; Spark appears in 10.7% of 214 comparable senior data engineering roles in United States.

Quick facts

Is the Senior Data Platform Engineer role remote?
It's hybrid — Komodo Health expects some on-site time in San Francisco, CA, United States.
What's the salary range?
Komodo Health lists $196,000–$230,000 for this role.
Where is the role based?
Komodo Health is hiring for this position in San Francisco, CA, United States.
What's the tech stack?
Joblaze extracted these technologies from the posting: AWS, Airflow, Python, SQL, Spark.
What seniority level is this role?
Komodo Health targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Senior Data Platform Engineer role at Komodo Health.

From the original posting

We Breathe Life Into Data

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.

$196,000—$230,000 USD
All Other US Locations:
$170,000—$200,000 USD

Komodo's AI Standard

Where You’ll Work

Standard company text repeated across Komodo Health's postings is omitted here.

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