Senior Engineer, Data Management
Hearst · New York, New York, United States · $140K–$150K/yr
Media Production · 10,001+ employees
About the role
The Senior Data Engineer will own the full lifecycle of complex data projects, including the design and development of secure, scalable data pipelines. They will also act as a technical resource for cross-functional teams and implement data governance and security standards across cloud environments.
What they look for
Requirements
Candidates must have 7+ years of experience in data engineering with strong proficiency in Python and cloud-based data solutions. A bachelor's degree in computer science or a related field is required, along with hands-on experience in generative AI and data integration tools.
Benefits
Full description
Why Hearst
Hearst is one of the nation's largest diversified media, information, and services companies, with more than 360 businesses spanning cable networks (A&E, HISTORY, ESPN), financial data (Fitch Group), healthcare information (Hearst Health), transportation, and digital services (iCrossing, KUBRA). Our strength comes from the range of backgrounds, disciplines, and perspectives our people bring together.
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.
