Lead Data Engineer (Healthcare Data & Audience Applications)

Exclusive opportunity

Onsite

Lead Data Engineer (Healthcare Data & Audience Applications)

Zeta Global

Lead Data Engineer (Healthcare Data & Audience Applications)

Skills

Google Cloud PlatformSQL QueriesData EngineeringDockerRubyPythonJavaMicroservicesMySQLKafkaSnowflakeDatabricksData AnalysisMachine LearningAIAWSKubernetesApache AirflowComplianceAzure

3 months ago

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Important information

Contract type:

Permanent

Salary:

$180,000 – $200,000 / year

Location:

United States

Work mode:

Onsite

Published on:

7 August 2026

What they need

Zeta Global is seeking a Lead Data Engineer to build and scale healthcare-focused applications and data systems that power audience intelligence, activation, measurement, and reporting across both HCP and DTC workflows
This is a hands-on technical leadership role operating at the intersection of distributed systems, data engineering, and healthcare domain constraints
You will design and deliver systems that integrate identity, audience data, and campaign performance while meeting strict requirements for privacy, compliance, and reliability
The ideal candidate brings strong system design depth, experience building data-intensive platforms, and the ability to lead through architecture and execution in regulated environments
Applications supporting HCP and patient / direct-to-consumer (DTC) audience discovery, segmentation, and activation
Scalable data pipelines for ingestion, normalization, and enrichment of healthcare datasets
Identity resolution and data linkage services across fragmented data sources
Reporting, attribution, and measurement systems connecting campaigns to outcomes
APIs and services enabling downstream activation, analytics, and partner integrations
Healthcare Cloud and data-mapping architecture across claims/Rx, NPI/HCP, patient, media-exposure, brand, and connector datasets
Healthcare-specific semantic cubes, governed views, data contracts, and domain APIs consumed by Vertical Apps; front-end applications should consume stable domain APIs rather than query raw stores or Cube directly
Identity resolution, match-rate measurement, medical-code mapping, and approved joins under CERT/HIPAA rules
Foundational data products for NPI onboarding, PLD reporting, script reporting, HCP/Patient intelligence, journeys, and Next Best Action
Define and maintain the healthcare data architecture, interface contracts, ADRs, schemas, and staged delivery plan
Lead ingestion and transformation patterns across Snowflake, Athena/S3, MySQL, and approved healthcare stores without duplicating shared platform capabilities
Partner with Data Cloud on source certification, partner-feed contracts, identity validation, raw-zone ownership, and data availability SLAs
Design healthcare base/vertical models and published/governed views, with row/member-level controls, account scoping, masking, and backward-compatible versioning
Set SLOs and operational readiness criteria; ensure dashboards, alerts, runbooks, rollback paths, and incident ownership are in place before release
Lead design and code reviews, mentor the Senior Data Engineer, and coordinate dependencies across the pod
Support compliance evidence, annual audits, US data-residency controls, and stoplight decisions: Start, Stop, or Requires CERT
Apply privacy-by-design principles across all systems handling PHI/PII
Partner with Product and Data teams to translate healthcare requirements into scalable architectures
Drive engineering best practices across testing, CI/CD, code quality, and operational excellence- Strong understanding of performance optimization and scalability trade-offs
Experience with workflow orchestration tools, such as Apache Airflow
Strong experience designing distributed systems, including microservices and event-driven architectures
Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure as code
Experience implementing observability practices, including logging, metrics, and tracing, as well as reliability patterns
Experience working with data warehouses and lakehouse platforms, such as Snowflake, Databricks, or similar technologies
Familiarity with containerization and orchestration technologies, including Docker and Kubernetes
Experience with streaming and batch processing technologies, such as Kafka, Spark, Flink, or similar tools
Deep understanding of data modeling, storage systems (OLTP and OLAP), and data-processing frameworks
Proficiency in backend development using Python, Java, or Ruby, as well as API design using REST or gRPC
8+ years of data engineering experience with increasing technical ownership
Understanding of healthcare data ecosystems (claims, provider, or audience datasets)
Proven track record of building and scaling data-intensive or distributed systems
Strong grasp of HIPAA, PHI/PII, and regulated data handling requirements
Experience with patient / DTC data workflows and privacy-aware systems
Ability to lead technically while remaining hands-on in implementation
Experience working with HCP data (provider identity, targeting, segmentation)
Strong collaboration skills across engineering, product, and data teams
Strong system design and architecture skills
Expert SQL and strong Python, Java; experience with batch and streaming patterns, orchestration, testing, and schema evolution
Technical standards for lineage, data quality, access control, masking, retention, auditability, observability, and cost
Experience building reporting or attribution systems tied to business outcomes
Experience working in regulated environments (healthcare strongly preferred)
Familiarity with identity graphs and data onboarding patterns
Experience with healthcare data providers or identity ecosystems
Background in AdTech, MarTech, or audience/data platforms
Experience with privacy-enhancing technologies (tokenization, clean rooms)
Exposure to ML/AI-driven data products or analytics systems

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