Pipeline Engineering & Component Ownership

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.

Design, Quality & Operational Reliability

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.

Domain & Stakeholder Partnership

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.

Data Engineer

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Definitivehc

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