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Data Engineer is a popular, early-career, generalist title at a large employer, raising applicant density.
Core data engineering skills transfer across industries, though governance and healthcare context raise moderate domain specificity.
Explicit experience cap and required bachelor's degree create moderate filtering alongside basic certification preference.
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Develop and maintain simple, standardized data pipelines and ETL/ELT components for data ingestion, transformation, and loading in batch or streaming scenarios.
Monitor pipeline schedules, SLAs, logs, perform routine failure investigations, and escalate unresolved issues to senior team members.
Collaborate with data analysts, scientists, and platform engineers to map data sources, refine requirements, and validate data outputs while applying security and governance controls.
Bachelor’s degree in computer science, data engineering, information systems, or related field, or equivalent experience.
Less than 2 years of experience required in data engineering, ETL/ELT development, data integration, or related domain.
Must have skills in building, testing, and monitoring ETL/ELT pipelines and performing data quality checks.
Certification in cloud, data, or technology fundamentals preferred but not mandatory.
Early-career data engineer comfortable working with standard frameworks and templates to build data pipelines.
Experience collaborating cross-functionally with analysts, scientists, and platform engineers to meet data delivery and quality requirements.
Ability to enforce security, privacy, and governance standards in data workflows, demonstrating operational discipline at a junior level.