Lead Data Engineer - Healthcare Data & Audience Applications

About the role

The Lead Data Engineer will build and scale healthcare‑focused applications and data systems that power audience intelligence, activation, measurement, and reporting for both HCP and direct‑to‑consumer workflows. This hands‑on technical leadership role designs distributed, privacy‑compliant architectures, integrates identity and campaign data, and guides a team through architecture, implementation, and operational excellence in a regulated environment.

About the company

Zeta Global is an AI‑powered Marketing Cloud that uses advanced AI and billions of consumer signals to help marketers acquire, grow, and retain customers. Through its Zeta Marketing Platform it unifies identity, intelligence, and omnichannel activation on a large proprietary database, serving enterprise customers across multiple verticals. Founded in 2007, headquartered in New York City with global offices.

Requirements

• Strong experience designing distributed systems, including microservices and event‑driven architectures.
• Deep understanding of data modeling, storage systems (OLTP and OLAP), and data‑processing frameworks.
• Experience with streaming and batch processing technologies such as Kafka, Spark, Flink, or similar.
• Proficiency in backend development using Python, Java, or Ruby and API design using REST or gRPC.
• Experience with workflow orchestration tools such as Apache Airflow.
• Experience with data warehouses and lakehouse platforms like Snowflake, Databricks, or similar.
• Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code.
• Familiarity with containerization and orchestration technologies including Docker and Kubernetes.
• Experience implementing observability practices (logging, metrics, tracing) and reliability patterns.
• Strong understanding of performance optimization and scalability trade‑offs.
• Experience working with HCP data (provider identity, targeting, segmentation).
• Experience with patient/DTC data workflows and privacy‑aware systems.
• Understanding of healthcare data ecosystems (claims, provider, or audience datasets).
• Familiarity with identity graphs and data onboarding patterns.
• Experience building reporting or attribution systems tied to business outcomes.
• Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements.
• Knowledge of technical standards for lineage, data quality, access control, masking, retention, auditability, observability, and cost.
• 8+ years of data engineering experience with increasing technical ownership.
• Expert SQL and strong Python, Java skills; experience with batch and streaming patterns, orchestration, testing, and schema evolution.
• Proven track record of building and scaling data‑intensive or distributed systems.
• Experience working in regulated environments (healthcare strongly preferred).
• Strong system design and architecture skills.
• Ability to lead technically while remaining hands‑on in implementation.
• Strong collaboration skills across engineering, product, and data teams.
• Experience with healthcare data providers or identity ecosystems (preferred).
• Background in AdTech, MarTech, or audience/data platforms (preferred).
• Experience with privacy‑enhancing technologies (tokenization, clean rooms) (preferred).
• Exposure to ML/AI‑driven data products or analytics systems (preferred).