Senior Data Platform Engineer (Healthcare Data)

Location: US remote, or hybrid in San Francisco or New York City. hirify.global also has hubs in Chicago.

Annual base pay: $196,000–$230,000 for the San Francisco Bay Area and New York City; $170,000–$200,000 for all other US locations. The role may also include performance-based bonuses and equity awards.

Company

hirify.global develops healthcare data products and software based on de-identified real-world patient data, algorithms, and clinical expertise.

What you will do

• Build, operate, and optimize large-scale production data pipelines using Python, SQL, Airflow, cloud infrastructure, and distributed processing frameworks.
• Transform healthcare claims, EHR, and reference datasets into trusted Healthcare Map data products and serving-ready assets.
• Improve reliability through data quality checks, validation, lineage, observability, monitoring, and alerting.
• Debug complex data, system, and performance issues across computationally intensive workflows.
• Partner with Data Product Quality, Product, Platform, and Engineering teams to deliver scalable technical solutions.
• Contribute to architecture, testing, documentation, CI/CD, production support, and downstream analytics and AI/ML use cases.

Requirements

• Healthcare data experience across claims, clinical, RWE, provider, patient, or life sciences datasets, including ICD-10, CPT, NDC, or NPI coding systems.
• Strong experience building, operating, and debugging production-grade data pipelines at scale.
• Advanced Python and SQL skills with Airflow or a similar workflow orchestration tool.
• Experience with Spark or comparable distributed data processing frameworks and AWS.
• Strong data quality, reliability, root-cause analysis, and production troubleshooting skills.
• Ability to communicate technical trade-offs and collaborate with engineering, product, and data partners; use of AI-assisted engineering tools such as ChatGPT, Gemini, or Claude is expected.

Nice to have

• Experience delivering external-facing data products through customers, APIs, serving layers, or production access patterns.
• Experience optimizing high-scale data architectures for performance, cost, versioning, and large-volume productization.
• Experience applying AI or agentic workflows to engineering, data quality, delivery, or operations.
• Experience working successfully in high-growth or ambiguous environments.

Culture & Benefits

• Hybrid work model with flexibility depending on the role and location.
• Comprehensive health, dental, and vision insurance.
• Flexible time off and holidays.
• 401(k) with company match, disability insurance, life insurance, and applicable leaves of absence.
• AI is integrated into daily engineering and business workflows.