Data Engineer

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.