Senior Data Engineer - Healthcare Data & Audience Applications

Zeta Global is an AI-Powered Marketing Cloud company that leverages advanced artificial intelligence to enhance marketing efficiency. They are seeking a Senior Data Engineer to build reliable and scalable data pipelines for the healthcare vertical, focusing on audience discovery, segmentation, and reporting.

Responsibilities:

• Design, develop, test, deploy, and operate production-grade pipelines for healthcare, identity, audience, media-exposure, and campaign-performance data using Python, SQL, Airflow, S3, Snowflake, and EMR
• Implement maintainable data models, transformations, governed views, and reusable datasets for provider identity, claims/Rx, NPI/HCP, media, brand, and connector data
• Deliver data products that support HCP and patient/DTC audience discovery, segmentation, activation, measurement, and reporting
• Build Airflow workflows with clear dependencies, retries, alerting, data-quality checks, and operational runbooks; use EMR for large-scale enrichment, normalization, and other compute-intensive workloads
• Write efficient SQL across Snowflake, Hive, and Athena, adapting to platform-specific syntax and query behavior
• Partner with product, analytics, data science, and platform teams to translate business and healthcare requirements into resilient technical solutions
• Implement data-quality controls, reconciliation checks, monitoring, alerting, and incident-response practices for critical data products
• Support data onboarding and integration for healthcare partners and internal sources, including validation, normalization, and source-to-target mapping
• Apply privacy-by-design practices for PHI/PII, including access controls, masking, approved joins, retention, and auditability
• Collaborate with the Lead Data Engineer on technical designs, code reviews, documentation, and delivery plans; mentor less-experienced engineers as needed
• Troubleshoot production issues and improve pipeline performance, reliability, and observability over time

Requirements:

• 5–8 years of hands-on data engineering experience, including ownership of production pipelines and data models, with experience working with healthcare data such as provider/HCP, claims, prescription, patient/DTC, or healthcare audience datasets
• Strong Python and expert SQL skills, with demonstrated experience building transformations, optimizing queries, and diagnosing data issues
• Hands-on experience with AWS data services, especially S3, and a modern cloud data warehouse; experience with Snowflake, Airflow, and EMR is strongly preferred
• Experience with data modeling, schema evolution, batch processing, orchestration, testing, CI/CD, and production support practices
• Proven ability to work with large, complex datasets and deliver reliable, well-documented data products
• Deep, practical knowledge of HIPAA, PHI/PII handling, privacy-by-design controls, and the operational requirements of regulated healthcare data environments
• Experience with AdTech/MarTech, identity resolution, audience onboarding, segmentation, data linkage, media measurement, attribution, or campaign reporting
• Ability to balance healthcare privacy constraints with the need for timely, accurate audience and performance insights
• Strong collaboration and communication skills across engineering, product, analytics, and business stakeholders
• Experience with healthcare data providers, identity ecosystems, tokenization, clean rooms, or privacy-enhancing technologies
• Experience with data cataloging, lineage, observability, and data-quality frameworks
• Experience with Docker, Kubernetes/EKS, infrastructure as code, and cloud deployment workflows
• Experience supporting reporting, attribution, or measurement products tied to campaign or business outcomes
• Exposure to ML/AI-enabled data products or analytics workflows