Data Engineer
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Job Description
Data Engineer building reliable pipelines and transformations for Definitive Healthcare’s healthcare data products. Supporting Claims and Consumer domains with Python, SQL, Spark, and cloud platforms.
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 from implementation through testing, deployment, documentation, and production support
- Troubleshoot pipeline failures, data quality issues, and performance problems; identify root causes and implement practical fixes
- Contribute to component-level technical designs, estimates, and implementation plans
- Apply practices for data modeling, testing, code review, observability, security, source control, CI/CD, and operational support
- Monitor pipeline performance and reliability; identify opportunities to improve quality, efficiency, and maintainability
- Develop working knowledge of Claims and Consumer data structures, transformations, 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 and support vendor-delivered data sources and customer issues
- Participate in code reviews, pairing, sprint activities, technical discussions, documentation, and knowledge sharing
- Support peers and less-experienced engineers through knowledge sharing and constructive review feedback
- Use approved AI-assisted development tools responsibly to improve productivity, documentation, test coverage, and code quality
Requirements:
- Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
- 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
- Experience with 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
- Preferred: healthcare data experience, including claims, pharmacy, eligibility, consumer, provider, or reference data
- Preferred: experience processing large datasets using lakehouse or medallion architecture patterns
- Preferred: experience deploying, operating, or supporting Spark workloads in Kubernetes or similar containerized environments
- Preferred: experience supporting enterprise data products, analytics platforms, or business-critical data services in regulated environments
- Preferred: experience onboarding or supporting vendor-delivered datasets and evaluating schema or downstream consumer impacts
- Preferred: experience using AI-assisted engineering tools to improve development productivity, testing, documentation, and code quality
Benefits:
- Company bonus or commission plan eligibility, depending on position
- Medical coverage
- Dental coverage
- Vision coverage
- Unlimited paid time off
- 401(k) plan with employer contribution
- Industry leading products
- Flexible and dynamic culture
- Definitive Cares community service group
- Competitive benefits package
- 401(k) match
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