高级数据工程师 - 医疗数据与受众应用
Senior Data Engineer - Healthcare Data & Audience Applications
**我们是谁**
Zeta Global（纽约证券交易所代码：ZETA）是基于人工智能的营销云平台，利用先进的人工智能（AI）和数万亿的消费者信号，帮助营销人员更高效地获取、增长和保留客户。通过 Zeta 营销平台（ZMP），我们的愿景是通过将身份识别、智能分析和全渠道激活整合到一个平台中，使复杂的营销变得简单——该平台由业内最大的专有数据库和 AI 驱动。我们的跨多个垂直领域的企业客户能够通过每个渠道为每位消费者提供个性化体验，从而提升营销活动的效果。Zeta 由 David A. Steinberg 和 John Sculley 于 2007 年创立，总部位于纽约市，并在全球设有办事处。如需了解更多信息，请访问 [www.zetaglobal.com](https://www.zetaglobal.com/)。
**职位概述**
Zeta Global 正在寻找一名高级数据工程师，为医疗保健垂直领域构建可靠、可扩展的数据管道和数据产品。你将是一名亲自动手的工程师，能够将复杂的医疗保健和营销数据集转化为用于受众发现、细分、激活、报告和评估的可信基础。
与工程和产品团队紧密合作，你将帮助实施团队的数据架构和工程标准，同时负责交付生命周期中的重要部分。你将参与设计和构建高质量、可投入生产的系统——而不是独自定义整体架构或技术路线图。
**主要职责**
- 使用 Python、SQL、Airflow、S3、Snowflake 和 EMR 设计、开发、测试、部署和运营适用于医疗保健、身份识别、受众、媒体曝光和活动表现数据的生产级管道。
- 实现可维护的数据模型、转换、受控视图和可重用数据集，涵盖供应商身份、索赔/处方、NPI/HCP、媒体、品牌和连接器数据。
- 提供支持 HCP 和患者/DTC 受众发现、细分、激活、评估和报告的数据产品。
- 构建具有清晰依赖关系、重试机制、警报、数据质量检查和操作运行手册的 Airflow 工作流；使用 EMR 处理大规模增强、标准化和其他计算密集型任务。
- 在 Snowflake、Hive 和 Athena 上编写高效的 SQL，适应各平台特定的语法和查询行为。
- 与产品、分析、数据科学和平台团队合作，
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**WHO WE ARE**
Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to [www.zetaglobal.com](https://www.zetaglobal.com/).
**ROLE OVERVIEW**
Zeta Global is seeking a Senior Data Engineer to build reliable, scalable data pipelines and data products for a healthcare vertical. You will be a hands-on engineer who turns complex healthcare and marketing datasets into trusted foundations for audience discovery, segmentation, activation, reporting, and measurement.
Working closely with the engineering and product team, you will help implement the team's data architecture and engineering standards while owning significant parts of the delivery lifecycle. You will contribute to well-designed, production-ready systems—not define the overall architecture or technical roadmap alone.
**Key Responsibilities**
- 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 that support HCP and patient/DTC audience discovery, segmentation, activation, measurement, and reporting.
- Build Airflow workflows with clear dependencies, retries, alerting, data-quality checks, and operational runbooks; use EMR for large-scale enrichment, normalization, and other 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 resilient technical solutions.
- Implement data-quality controls, reconciliation checks, monitoring, alerting, and incident-response practices for critical data products.
- 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 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 over time.
**Core Technical Environment**
- Data storage & warehouse: Snowflake Native and Amazon S3.
- Orchestration: Apache Airflow for general pipeline setup and scheduling.
- Heavy processing: Amazon EMR for targeted, compute-intensive jobs.
- Programming: Python for Airflow pipelines and supporting data engineering services.
- Querying: SQL in Snowflake, Hive, and Athena.
**Qualifications**
- 5–8 years of hands-on data engineering experience, including ownership of production pipelines and data models, with experience working with healthcare data such as provider/HCP, claims, prescription, patient/DTC, or healthcare audience datasets.
- Strong Python and expert SQL skills, with demonstrated experience building transformations, optimizing queries, and diagnosing data issues.
- Hands-on experience with AWS data services, especially S3, and a modern cloud data warehouse; experience with Snowflake, Airflow, and EMR is strongly preferred.
- Experience with data modeling, schema evolution, batch processing, orchestration, testing, CI/CD, and production support practices.
- Proven 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 the 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 the need for 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, or privacy-enhancing technologies.
- Experience with data cataloging, lineage, observability, and data-quality frameworks.
- Experience with Docker, Kubernetes/EKS, infrastructure as code, and cloud deployment workflows.
- Experience supporting reporting, attribution, or measurement products tied to campaign or business outcomes.
- Exposure to ML/AI-enabled data products or analytics workflows.
**BENEFITS & PERKS**
- Unlimited PTO
- Excellent medical, dental, and vision coverage
- Employee Equity
- Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!
**SALARY RANGE**
The salary range for this role is $140,000 - $160,000, depending on location and experience.
**PEOPLE & CULTURE AT ZETA**
Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.
We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: [https://zetaglobal.com/blog/a-look-into-zetas-ergs/](https://zetaglobal.com/blog/a-look-into-zetas-ergs/)
**ZETA IN THE NEWS!**
[https://zetaglobal.com/press/?cat=press-releases](https://zetaglobal.com/press/?cat=press-releases)
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