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Mid-level, metro Data Engineer role with broad Databricks/PySpark requirements attracts many qualified applicants.
Core data engineering skills are transferable across industries despite enterprise platform specifics.
Required Databricks, PySpark, and entity-resolution skills create strict technical filters.
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Build and enhance enterprise data pipelines ingesting data into Databricks Unity Catalog and Delta Lake.
Strengthen remediation and matching layers in data pipelines, including automatic remediation with D&B DataBlocks and LLM-assisted processes.
Support the CMG redesign project focusing on data engineering workflows.
Strong experience with PySpark, Python, and Databricks (Unity Catalog & Delta Lake).
Hands-on experience with enterprise data pipelines, entity resolution/matching, and data remediation.
Experience integrating APIs into data engineering workflows.
Work Experience Required: 5+ years in Data Engineering (preferred but not explicitly mandatory).
Experienced in large-scale enterprise data platforms and modern data architectures.
Familiarity or experience with AI-enabled or LLM-assisted data engineering workflows.
Ability to work on complex enterprise data strategy initiatives involving advanced data remediation and matching techniques.