Senior Data Engineer – Healthcare Data, Audience Applications

🕒 Agosto 10

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $140.000 - $160.000 / ano

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

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Zeta Global

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2007

💼 Consultoria

📦 Logística

✈️ Turismo

💰 Post-IPO Debt em 2024-09

Consulting • Logistics • Travel

A Zeta Global é uma nuvem de marketing impulsionada por IA que aproveita a IA proprietária e trilhões de sinais de consumidores para adquirir, crescer e reter clientes de maneira mais eficiente. A Zeta Marketing Platform (ZMP) oferece um conjunto abrangente de ferramentas, incluindo gerenciamento de dados, plataformas de dados de clientes (CDP), provedores de serviço de e-mail (ESP) e processamento de sinal digital (DSP), para criar experiências personalizadas para clientes e melhorar os resultados de marketing. A Zeta enfatiza o marketing omnichannel, inteligência de cliente e estratégias de marketing orientadas por dados, fazendo parceria com marcas, agências e editoras em todo o mundo para acelerar o crescimento e o engajamento da marca. Sua plataforma é projetada para enfrentar desafios complexos de marketing com soluções para aquisição, crescimento e retenção de clientes por meio de IA preditiva e dados de consumidores acionáveis.

Descrição

• 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 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 and compute-intensive workloads. • Write efficient SQL across Snowflake, Hive, and Athena. • 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. • Support healthcare data onboarding and integration, 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.

🎯 Requisitos

• 5–8 years of hands-on data engineering experience, including ownership of production pipelines and data models, with healthcare data experience. • Strong Python and expert SQL skills, including transformations, query optimization, and data issue diagnosis. • Hands-on experience with AWS data services, especially S3, and a modern cloud data warehouse. • 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 practical knowledge of HIPAA, PHI/PII handling, privacy-by-design controls, and 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. • 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.

🏖️ Benefícios

• Unlimited PTO • Excellent medical, dental, and vision coverage • Employee Equity • Employee Discounts • Virtual Wellness Classes • Pet Insurance