Zeta Global seeks a Senior Data Engineer to build scalable data pipelines and products for healthcare data. Responsibilities include designing, developing, testing, deploying, and operating production-grade pipelines using Python, SQL, Airflow, S3, Snowflake, and EMR. The role involves implementing data models, transformations, and governed views for healthcare and marketing datasets, supporting audience discovery, segmentation, activation, measurement, and reporting. The engineer will build Airflow workflows with retries, alerting, and data-quality checks, write efficient SQL across Snowflake, Hive, and Athena, and collaborate with cross-functional teams to translate business requirements into technical solutions. The role requires applying privacy-by-design practices for PHI/PII and supporting data onboarding and integration. Qualifications include 5-8 years of data engineering experience with healthcare data, strong Python and SQL skills, experience with AWS data services, Snowflake, Airflow, EMR, data modeling, batch processing, CI/CD, and knowledge of HIPAA and privacy controls. Preferred experience includes healthcare data providers, data cataloging, Docker, Kubernetes/EKS, and ML/AI-enabled data products. Benefits include unlimited PTO, medical/dental/vision coverage, employee equity, discounts, wellness classes, and pet insurance. Salary range is $140,000 - $160,000. The position is remote in the United States.
What you'll do
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Design, develop, test, deploy, and operate production-grade pipelines for healthcare, identity, audience, media-exposure, and campaign-performance data
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 supporting HCP and patient/DTC audience discovery, segmentation, activation, measurement, and reporting
Build Airflow workflows with dependencies, retries, alerting, data-quality checks, and operational runbooks
Use EMR for large-scale enrichment, normalization, and 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 technical solutions
Implement data-quality controls, reconciliation checks, monitoring, alerting, and incident-response practices
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 Lead Data Engineer on technical designs, code reviews, documentation, and delivery plans; mentor less-experienced engineers
Troubleshoot production issues and improve pipeline performance, reliability, and observability
Requirements
5–8 years of hands-on data engineering experience including ownership of production pipelines and data models
Experience working with healthcare data such as provider/HCP, claims, prescription, patient/DTC, or healthcare audience datasets
Strong Python and expert SQL skills with experience building transformations, optimizing queries, and diagnosing data issues
Hands-on experience with AWS data services, especially S3, and modern cloud data warehouses
Experience with Snowflake, Airflow, and EMR preferred
Experience with data modeling, schema evolution, batch processing, orchestration, testing, CI/CD, and production support
Ability to work with large, complex datasets and deliver reliable, well-documented data products
Deep knowledge of HIPAA, PHI/PII handling, privacy-by-design controls, and 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 timely, accurate audience and performance insights
Strong collaboration and communication skills across engineering, product, analytics, and business stakeholders
Tech stack
PythonSQLAirflowAmazon S3SnowflakeAmazon EMRHiveAthenaDockerKubernetesEKSinfrastructure as codeCI/CD
