Senior Data Engineer – Healthcare Data, Audience Applications

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, test, deploy, and manage production-grade pipelines for healthcare, identity, audience, media exposure, and campaign performance data utilizing Python, SQL, Airflow, S3, Snowflake, and EMR.

• Create maintainable data models, transformations, governed views, and reusable datasets for provider identity, claims/Rx, NPI/HCP, media, brand, and connector data.

• Produce data products that facilitate HCP and patient/DTC audience discovery, segmentation, activation, measurement, and reporting.

• Construct Airflow workflows with dependencies, retries, alerting, data quality checks, and operational runbooks; leverage EMR for large-scale enrichment and compute-intensive tasks.

• Write optimized SQL across Snowflake, Hive, and Athena.

• Collaborate with product, analytics, data science, and platform teams to transform business and healthcare requirements into robust technical solutions.

• Establish data quality controls, reconciliation checks, monitoring, alerting, and incident response practices.

• Assist in healthcare data onboarding and integration, encompassing validation, normalization, and source-to-target mapping.

• Employ privacy-by-design principles for PHI/PII, including access controls, masking, approved joins, retention, and auditability.

• Work with the Lead Data Engineer on technical designs, code reviews, documentation, and delivery plans; mentor junior engineers as needed.

• Diagnose production issues and enhance pipeline performance, reliability, and observability.

⛳️ Requirements

• 5–8 years of practical data engineering experience, including responsibility for production pipelines and data models, with a focus on healthcare data.

• Proficient in Python and expert in SQL, including transformations, query optimization, and data issue diagnosis.

• Hands-on experience with AWS data services, particularly S3, and a contemporary cloud data warehouse.

• Familiarity with data modeling, schema evolution, batch processing, orchestration, testing, CI/CD, and production support.

• Capability to work with large, intricate datasets and deliver reliable, well-documented data products.

• Comprehensive understanding of HIPAA, PHI/PII handling, privacy-by-design controls, and regulated healthcare data environments.

• Knowledge of AdTech/MarTech, identity resolution, audience onboarding, segmentation, data linkage, media measurement, attribution, or campaign reporting.

• Ability to navigate healthcare privacy constraints while providing timely and accurate audience and performance insights.

• Excellent collaboration and communication skills with engineering, product, analytics, and business stakeholders.

• Preferred: experience with healthcare data providers, identity ecosystems, tokenization, clean rooms, privacy-enhancing technologies, data cataloging, lineage, observability, data quality frameworks, Docker, Kubernetes/EKS, infrastructure as code, cloud deployment workflows, reporting/attribution/measurement products, or ML/AI-enabled data products.

🏝️ Benefits

• Unlimited PTO

• Excellent medical, dental, and vision coverage

• Employee Equity

• Employee Discounts

• Virtual Wellness Classes

• Pet Insurance