Senior Engineer, Data Management

Hearst Magazines; New York (NY); On-site; USD 140,000 - 150,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k)

Paid holidays and PTO

Employee assistance programs

Job summary

Hearst Magazines seeks a Senior Data Engineer to own end-to-end data projects, from analysis through production support. You will build scalable pipelines, APIs, and data platforms across Snowflake, Fabric, and Databricks while ensuring governance and security across AWS/Azure/GCP.

You’ll mentor engineers, collaborate with analysts and data scientists, implement DevSecOps practices, and help shape the data/AI roadmap for Hearst Technology Services.

Qualifications

• 7+ years building production data pipelines and data engineering.
• Hands-on with generative AI tools applied to data engineering workflows.
• Experience on AWS, Azure, or GCP cloud platforms.
• ETL, data modeling, and modular component design for complex systems.
• Containerization experience (Docker/Kubernetes).
• Data governance, security, and quality standards, including PHI/PII/PCI.
• Informatica IDMC/MDM or similar tools.
• Strong data structures, algorithms, and software architecture knowledge.
• Ability to translate requirements with analysts, scientists, and stakeholders.
• Experience with Agile and DevSecOps (Jira/Scrum/Kanban).

Responsibilities

• Design and build scalable, secure data pipelines for large data volumes.
• Develop APIs and database logic to automate data fetch, transform, and storage.
• Leverage generative AI to accelerate pipelines across Snowflake, Fabric, and Databricks.
• Create modular components for data and AI apps deployed via Docker/Kubernetes.
• Build data solutions across AWS, Azure, and Google Cloud.
• Apply data governance, security, and quality standards across clouds.
• Handle PHI/PII/PCI data per compliance requirements.
• Collaborate with analysts, scientists, and IT to power new data products.
• Provide technical leadership: mentor engineers, review designs, and guide production issues.
• Apply DevSecOps practices and Agile methods to plan and deliver work.
• Monitor and improve performance, resiliency, and scalability as data grows.

Skills

Python

Data pipelines

Cloud platforms AWS/Azure/GCP

ETL & data modeling

Containerization Docker/Kubernetes

Data governance & security

Informatica IDMC/MDM

Agile/DevSecOps Jira/Scrum/Kanban

Stakeholder communication

Education

Bachelor’s degree in CS/IS or related field

Master’s degree preferred

Tools

Docker

Kubernetes

Informatica IDMC/MDM

Snowflake

Microsoft Fabric

Databricks

Jira

Job description

Why Hearst

Hearst is one of the nation's largest diversified media, information and services companies, with a portfolio of more than 360 businesses worldwide. Our consumer businesses include television stations, newspapers, magazines and ownership stakes in cable networks. Our business-to-business companies include Fitch Group, Hearst Health and Hearst Transportation. Across our businesses, you'll find opportunities to do meaningful work, grow your career and make an impact.

About This Role

Hearst Technology Services is looking for a Senior Data Engineer to help shape our data and AI technology roadmap. You'll own the full lifecycle of complex data projects — from analysis and design through development and production support — building pipelines and integrations that move data securely and reliably across cloud platforms. You'll also help design the tooling that extracts, transforms, and governs data from both internal systems and external sources, and act as a technical resource for engineers, analysts, and data scientists across the business.

What You'll Do

• Design and build scalable, secure pipelines that ingest, transform, and move large volumes of structured and unstructured data across systems.

• Build APIs and complex database logic to automate the fetch, transformation, and storage of data in multiple formats.

• Use generative AI tools to accelerate the development, testing, and maintenance of pipelines across Snowflake, Microsoft Fabric, and Databricks.

• Architect and maintain modular, reusable components that power larger data and AI applications, deployed via containerized workflows (Docker/Kubernetes) where applicable.

• Design, build, and maintain data solutions across AWS, Azure, and/or Google Cloud.

• Implement data quality, security, and governance standards consistently across cloud environments, including integrations between platforms like Informatica IDMC and MDM.

• Securely handle PHI, PII, and PCI data in line with regulatory and internal compliance requirements.

• Partner with data analysts, data scientists, and IT operations to build tools and pipelines that power new data and AI products — including downstream reporting and BI use cases.

• Provide technical leadership on projects: mentor engineers, review designs, and offer guidance on complex technical or production issues.

• Apply DevSecOps practices and Agile methodologies (Jira, Scrum/Kanban) to plan and deliver work.

• Monitor and improve application performance, resiliency, and scalability as data volumes grow.

What You'll Bring

Required

• 7+ years building production data pipelines, with strong Python (or equivalent) and both relational and non-relational database experience.

• Hands-on experience with generative AI tools applied to data engineering workflows.

• Experience designing and maintaining data solutions on at least one major cloud platform (AWS, Azure, or GCP).

• Experience with ETL tools, data modeling, and building reusable, modular components for complex systems.

• Working knowledge of containerization (Docker/Kubernetes) or similar deployment practices.

• Experience implementing data governance, security, and quality standards, ideally including regulated data (PHI/PII/PCI).

• Experience with Informatica IDMC/MDM or comparable data integration and master-data tooling.

• Solid grounding in data structures, algorithms, and software architecture, with experience documenting and testing complex systems.

• Comfort working directly with data analysts, data scientists, and business stakeholders to translate requirements into pipelines and products.

• Experience with Agile delivery (Jira, Scrum, or Kanban) and DevSecOps practices.

Nice to Have

• Prior experience leading a small team of data engineers/analysts.

• Experience with data classification and taxonomy tools, particularly within Informatica.

• Exposure to BI/reporting tools (e.g., Power BI, Tableau, Looker) to support downstream analytics consumers.

Qualifications

• Bachelor’s degree in computer science, Information Systems, or a related field; Master’s preferred.

• 7+ years of experience as a Data Engineer, including senior or lead-level project ownership.

In accordance with applicable law, Hearst is required to include a reasonable estimate of the compensation for this role if hired in New York City. The reasonable estimate, if hired in New York City, is $140,000-$150,000. Please note this information is specific to those hired in New York City. If this role is open to candidates outside of New York City, the salary range would be aligned to that specific location. A final decision on the successful candidate’s starting salary will be based on a number of permissible, non-discriminatory factors, including but not limited to skills and experience, training, certifications, and education. Hearst provides a competitive benefits package, including medical, dental, vision, disability and life insurance, 401(k), paid holidays and paid time off, employee assistance programs, and more.