Data Engineer - MarTech Retail Media Network Overview Client is looking for a Data Engineer to join the MarTech team! MarTech builds and operates the platforms and capabilities that power how Client reaches, engages, and personalizes the experience for millions of customers every day across our owned web and app, in-store and pump screens, CRM, retail media, and paid channels. If you get excited about bringing structure to complex, cross-team programs and driving them from plan to delivery, read on. About the job: You'll be joining a multidisciplinary MarTech organization spanning four connected work streams, Retail Media (RMN), CRM & Campaigns, Personalization & Web, and a shared MarTech Foundation team, alongside product managers, solution architects, software and data engineers, and QA who build the systems that activate marketing across every customer touchpoint. As a Data Engineer, you will partner with data science, architecture, MarTech engineering, and platform owners to close upstream data-quality, freshness, and coverage gaps that limit personalization today. This role directly enables timely, accurate, and compliant use of customer data across every marketing channel. 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. Required 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. 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. Preferred Qualifications Experience with reverse-ETL/activation and identity resolution (e.g., Hightouch, LiveRamp/UID2). 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.