Senior Data Engineer – Marketing Data & Clean Room Technologies

Role Overview We are looking for an experienced Data Engineer with expertise in privacy-focused data collaboration and cloud-based data engineering. The ideal candidate will have experience working with clean room technologies, identity resolution, and scalable data pipelines while ensuring compliance with modern data privacy standards. Key Responsibilities • Design, develop, and optimize secure data workflows for marketing and analytics use cases. • Build and maintain cloud-native data pipelines to support data ingestion, transformation, and reporting. • Develop and optimize SQL queries, reusable logic, and user-defined functions (UDFs) within privacy-controlled data environments. • Work with identity resolution frameworks to improve data matching accuracy and audience activation. • Collaborate with analytics, marketing, and engineering teams to deliver privacy-compliant data solutions. • Ensure data processing aligns with regulatory and governance requirements across controlled data environments. • Monitor pipeline performance, troubleshoot issues, and implement improvements for scalability and reliability. Required Qualifications • 5–7 years of experience in Data Engineering, Marketing Technology, Data Platforms, or related domains. • At least 2 years of practical experience working with data collaboration platforms or clean room technologies such as LiveRamp Clean Room (Habu), InfoSum, AWS Clean Rooms, Google Ads Data Hub, or comparable solutions. • Strong hands-on experience writing advanced SQL queries for complex analytical workloads. • Experience creating reusable query logic, UDFs, or privacy-aware analytical models within secure data-sharing environments. • Good understanding of privacy-preserving analytics, including aggregation thresholds, suppression techniques, and secure reporting methodologies. • Familiarity with identity resolution strategies, persistent identifiers, deterministic/probabilistic matching, and match optimization techniques. • Experience building scalable ETL/ELT pipelines using Python, Spark, or similar data processing frameworks. • Hands-on experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure. • Understanding of data privacy and governance frameworks applicable to regulated industries. Preferred Skills • Experience supporting customer analytics, advertising technology, or audience measurement initiatives. • Exposure to financial services, healthcare, or other highly regulated environments. • Strong analytical mindset with excellent troubleshooting and problem-solving abilities. • Effective communication and stakeholder collaboration skills.