Data Engineer

Definitive Healthcare • Framingham, MA

3d

About The Position

Definitive Healthcare is seeking a Data Engineer to build, maintain, and support reliable data pipelines and transformations that power healthcare data products and customer-facing solutions. The role is accountable for the quality, reliability, and timely delivery of assigned pipeline components and data changes across Claims and Consumer data domains. Working with engineering and domain experts, the Data Engineer develops moderate-complexity solutions, troubleshoots pipeline and data quality issues, and supports production operations. The role works with growing independence, follows established standards, communicates progress and blockers, and collaborates with engineers, analysts, Product, Support, and data consumers.

The Data Engineer owns defined pipeline components from implementation through testing, deployment, documentation, and production support, with technical guidance as needed. The role contributes to technical designs and implementation plans, applies team engineering practices, monitors pipeline reliability, and assesses the downstream effects of data and schema changes. It also participates in code reviews, pairing, sprint activities, technical discussions, documentation, and knowledge sharing, and uses approved AI-assisted development tools responsibly.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• At least 2 years of Data Engineering, Software Engineering, or related experience building and supporting production data solutions.
• Proficiency in Python and SQL, with hands-on experience developing and maintaining production data pipelines.
• Experience with Apache Spark/PySpark or equivalent distributed data processing technologies.
• Experience with cloud platforms such as AWS, Azure, or GCP and modern data platforms such as Databricks, Snowflake, Delta Lake, or equivalent technologies.
• Experience with workflow orchestration technologies such as Airflow, Argo, or equivalent platforms.
• Working knowledge of relational databases, data modeling, testing, code review, observability, source control, CI/CD, and production support practices.
• Ability to own defined technical work, troubleshoot issues, collaborate effectively, and communicate progress, risks, and blockers.

Nice To Haves

• Healthcare data experience, including claims, pharmacy, eligibility, consumer, provider, or reference data.
• Experience processing large datasets using lakehouse or medallion architecture patterns.
• Experience deploying, operating, or supporting Spark workloads in Kubernetes or similar containerized environments.
• Experience supporting enterprise data products, analytics platforms, or business-critical data services in regulated environments.
• Experience onboarding or supporting vendor-delivered datasets and evaluating schema or downstream consumer impacts.
• Experience using AI-assisted engineering tools to improve development productivity, testing, documentation, and code quality.

Responsibilities

• Build, maintain, test, and support moderate-complexity ETL/ELT pipelines, transformations, and data components using Python, SQL, Spark/PySpark, and related technologies.
• Own defined pipeline components through implementation, testing, deployment, documentation, and production support, with technical guidance as needed.
• Troubleshoot pipeline failures, data quality issues, and performance problems; identify root causes and implement practical, maintainable fixes.
• Contribute to component-level technical designs, estimates, and implementation plans while following established architecture and engineering standards.
• Apply team practices for data modeling, testing, code review, observability, security, source control, CI/CD, and operational support.
• Monitor pipeline performance and reliability, surface risks and blockers, and identify opportunities to improve quality, efficiency, and maintainability.
• Develop working knowledge of Claims and Consumer data structures, source-to-target transformations, pipeline dependencies, and data quality standards.
• Collaborate with engineers, QA, analysts, Product, Support, and data consumers to clarify requirements, resolve issues, and deliver reliable data changes.
• Assess downstream impacts of data and schema changes, communicate technical status, and support vendor-delivered data sources and customer issues.
• Participate in code reviews, pairing, sprint activities, technical discussions, documentation, and team knowledge sharing.
• Support peers and less-experienced engineers by sharing knowledge, providing constructive review feedback, and modeling effective engineering practices.
• Use approved AI-assisted development tools responsibly to improve productivity, documentation, test coverage, and code quality while following team review standards.

Benefits

• Medical coverage
• Dental coverage
• Vision coverage
• Unlimited paid time off
• 401(k) plan with employer contribution
• Potential eligibility for a company bonus or commission plan, depending on position

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level