Data Engineer

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Develop, maintain, test, and support ETL/ELT pipelines, transformations, and data components of moderate complexity.

• Take ownership of designated pipeline components from their implementation through testing, deployment, documentation, and production support.

• Diagnose pipeline failures, address data quality issues, and resolve performance challenges; determine root causes and implement sustainable solutions.

• Contribute to technical designs, provide estimates, and create implementation plans.

• Implement best practices for data modeling, testing, code review, observability, security, source control, CI/CD, and operational support.

• Monitor the performance and reliability of pipelines, identify risks and obstacles, and enhance quality, efficiency, and maintainability.

• Acquire a practical understanding of Claims and Consumer data structures, transformations, dependencies, and quality benchmarks.

• Collaborate effectively with engineers, QA, analysts, Product, Support, and data consumers.

• Evaluate the downstream effects of data and schema modifications, and assist with vendor-supplied data sources and customer-related issues.

• Engage in code reviews, pairing sessions, sprint activities, technical discussions, documentation efforts, and knowledge sharing.

• Mentor less-experienced engineers through knowledge sharing and constructive feedback during reviews.

• Responsibly utilize approved AI-assisted development tools.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

• Over 2 years of experience in Data Engineering, Software Engineering, or a related field, focused on building and supporting production data solutions.

• Strong proficiency in Python and SQL.

• Practical experience in developing and maintaining production data pipelines.

• Familiarity with Apache Spark/PySpark or similar distributed data processing technologies.

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Knowledge of technologies like Databricks, Snowflake, Delta Lake, or their equivalents.

• Experience with workflow orchestration tools such as Airflow or Argo.

• Understanding of relational databases, data modeling, testing, code review, observability, source control, CI/CD, and production support methodologies.

• Capability to manage technical tasks, troubleshoot issues, collaborate effectively, and communicate progress, risks, and obstacles.

• Experience with healthcare data, including claims, pharmacy, eligibility, consumer, provider, or reference data (preferred).

• Familiarity with lakehouse or medallion architecture patterns (preferred).

• Background in supporting Spark workloads in Kubernetes or similar environments (preferred).

• Experience with enterprise data products or regulated data services (preferred).

• Knowledge of onboarding vendor-delivered datasets and assessing schema or downstream impacts (preferred).

• Experience using AI-assisted engineering tools (preferred).

🏝️ Benefits

• Medical coverage.

• Dental coverage.

• Vision coverage.

• Unlimited paid time off.

• 401(k) plan with employer contribution/match.

• Eligibility for company bonus or commission plan, depending on the position.

• Access to industry-leading products.

• Flexible and dynamic workplace culture.

• Opportunities for community service through Definitive Cares.

• Competitive benefits package.

• Excellent healthcare benefits.