Data Engineer Lead
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Job Description
Job Description
Build and maintain scalable data solutions to support marketing analytics and audience activation initiatives, with a strong focus on Databricks, governed data structures, reusable components, and reliable data pipelines.
The ideal candidate has strong experience working with Databricks, Git-based development workflows, marketing performance data, customer identity matching, and data governance. You will work with data from multiple enterprise sources, transform legacy audience logic into governed definitions, and build reliable data products that support analytics and downstream activation.
Responsibilities
• Develop and maintain scalable data pipelines in Databricks, using Unity Catalog and Delta.
• Curate Genie spaces and semantic layers, including table and column metadata, certified metric definitions, example SQL, and trusted assets.
• Maintain and refactor existing Git/GitHub repositories, developing modular and reusable data components.
• Implement CI/CD workflows for Databricks solutions, including promotion from development to controlled UAT environments.
• Model marketing performance data including email events, campaign and promotion history, offers, packages, and tours.
• Build point-in-time audience histories and connect marketing sends with downstream sales outcomes.
• Develop data solutions at the person and household grain, using ID crosswalks and match rules based on existing identity resolution outputs.
• Implement suppression and consent requirements, including Do Not Email rules, marketability flags, and PII handling.
• Ingest and integrate data from SQL Server enterprise data warehouses and translate legacy SQL audience logic into governed definitions.
• Deliver audiences from Databricks to Adobe Campaign or Segment, including service accounts, encryption, and auditing.
• Profile unfamiliar data sources independently, producing data dictionaries and ERDs and verifying data availability and structure.
• Develop data quality tests and validated query/result sets to support reliable datasets and agent evaluation.
• Collaborate with analytics, engineering, marketing, data, and security teams to improve data solutions and processes.
Requirements
Function: Marketing
Experience Level: Mid-Senior Level