Data Engineer

About the role

This position will design, build, and scale a Customer Data Platform (CDP) that delivers a true Customer 360. The role will be responsible for data engineering, analytics enablement, and growth strategy, powering cross-sell, CLV measurement, and propensity modeling across product lines.

Responsibilities

• Architect and develop a Customer 360 using Salesforce Data 360 (formerly Data Cloud), integrating first-party and digital data (GA4, CRM, transactional, product usage).
• Ensure data quality, governance, and compliance (PII handling, consent, privacy).
• Translate business questions into data structures that support analytics, AI/ML, and activation.
• Develop and deploy propensity models to support customer segmentation, targeting, and personalization initiatives.
• Build scalable data pipelines (batch and zero-copy) to ingest, unify, and activate customer data.
• Build identity resolution and data harmonization models to support cross-product insights and personalization.
• Partner with analytics, marketing, and product teams to enable cross-sell identification, CLV modeling, and propensity-to-buy use cases.
• Contribute to CDP roadmap decisions and evaluate emerging data technologies.

Requirements

• Bachelor's degree in Information Systems or a related field.
• 7+ years of data engineering experience, including 5+ years with enterprise CDPs and 3+ years with Salesforce Data Cloud (or equivalent).
• Strong expertise in SQL, cloud data warehouses (e.g., BigQuery), and building analytics- and activation-ready data pipelines using Python, dbt, and modern data platforms.
• Experience with digital and behavioral data (e.g., GA4), identity resolution, customer data modeling, and enterprise-scale data integration.
• Hands-on experience with APIs, ETL/ELT tools, and Salesforce Data Cloud ingestion, modeling, and governance.
• Ability to design scalable data architectures independently while balancing technical best practices with business outcomes.