Key Responsibilities:
• Design, build, and operate scalable batch and real-time data pipelines in Databricks and related tooling to support audience, personalization, and measurement use cases.
• Build and maintain data models, feature/attribute pipelines, and marketing data feeds to decisioning systems and measurement platforms.
• Implement data-quality validation, monitoring, and change management so segments, flags, and attributes are accurate and trustworthy.
• Deliver governed customer attributes and audiences to activation platforms (e.g., Hightouch, Salesforce Marketing Cloud) with clear ownership and documentation.
• Partner with data science to productionize model features and with architecture to align on data contracts and identity resolution.
• Support privacy and compliance requirements across all data flows.
• Provide leadership-ready status, roadmap, and metrics reporting, and prepare decision memos that drive cross-team and leadership alignment.
Basic Qualifications:
- 3+ years of experience in a data engineering role required.
- Strong SQL and proficiency in a programming language for data engineering (e.g., Python or Scala).
- Hands-on experience with Databricks/Spark, data lake/warehouse design, and pipeline orchestration.
- Experience with real-time/streaming data (e.g., Kafka) and event-driven architectures.
- Experience with reverse-ETL/activation and identity resolution (e.g., Hightouch, LiveRamp/UID2) preferred.
- Understanding of data modeling, data quality, governance, and change management.
- Familiarity with marketing/customer data concepts (C360, RFM, LTV, loyalty) and compliant handling of PII.
Extra Credit:
• Experience in a MarTech, digital marketing, personalization, CRM, or retail-media ecosystem.
• Familiarity with platforms in our stack, e.g., Salesforce Marketing Cloud (SFMC), Databricks, Hightouch, Kafka, Contentstack / CMS & DAM, LiveRamp / UID2.
• Retail or convenience-retail industry experience.
Never miss an opportunity! Create an alert based on the job you applied for.
