Data Engineer: Build Scalable Cloud ETL Pipelines

Definitive Healthcare Corp.; Boston (MA); Hybrid; USD 93,000 - 141,000; Full time

Job summary

Definitive Healthcare is seeking a Data Engineer to build, maintain, and support reliable data pipelines powering healthcare data products and customer-facing solutions.

This role requires hands-on experience with Python, SQL, Spark/PySpark on cloud platforms, and modern orchestration tools. You’ll collaborate with engineering, product, and data consumers to deliver high-quality data changes and reliable production support.

Qualifications

• 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 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.

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 with technical guidance as needed.
• Troubleshoot pipeline failures, data quality issues, and performance problems; identify root causes with support 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 early, 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 expected 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 clearly, and support vendor-delivered data sources and customer issues.
• Participate actively 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.

Skills

Python

SQL

Spark/PySpark

Airflow

Argo

Databricks

Snowflake

Delta Lake

AWS

Azure

GCP

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience

Tools

Airflow

Argo

Job description

Definitive Healthcare is seeking a Data Engineer to build, maintain, and support reliable data pipelines powering healthcare data products and customer-facing solutions.

This role requires hands-on experience with Python, SQL, Spark/PySpark on cloud platforms, and modern orchestration tools. You’ll collaborate with engineering, product, and data consumers to deliver high-quality data changes and reliable production support.