Senior Engineer, Data Management

Hearst•New York, NY

1d•$140,000 - $150,000

About The Position

Hearst Technology Services is seeking a Senior Data Engineer to help shape its data and AI technology roadmap. The role owns the full lifecycle of complex data projects, from analysis and design through development and production support, and builds pipelines and integrations that move data securely and reliably across cloud platforms. It also involves designing tools to extract, transform, and govern data from internal systems and external sources, and serving as a technical resource for engineers, analysts, and data scientists across the business.

Requirements

7+ years of experience building production data pipelines, with strong Python or equivalent skills and experience with relational and non-relational databases.
Hands-on experience applying generative AI tools 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, such as Docker/Kubernetes, or similar deployment practices.
Experience implementing data governance, security, and quality standards, ideally for regulated data such as PHI, PII, or 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.
Ability to work 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.
Bachelor’s degree in computer science, Information Systems, or a related field.
7+ years of experience as a Data Engineer, including senior- or lead-level project ownership.

Nice To Haves

Prior experience leading a small team of data engineers or analysts.
Experience with data classification and taxonomy tools, particularly within Informatica.
Exposure to BI/reporting tools such as Power BI, Tableau, or Looker.

Responsibilities

Design and build scalable, secure pipelines to ingest, transform, and move large volumes of structured and unstructured data across systems.
Build APIs and complex database logic to automate fetching, transforming, and storing 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 for larger data and AI applications, using containerized workflows such as Docker and Kubernetes where applicable.
Design, build, and maintain data solutions across AWS, Azure, and/or Google Cloud.
Implement data quality, security, and governance standards across cloud environments, including integrations such as Informatica IDMC and MDM.
Handle PHI, PII, and PCI data securely in accordance with regulatory and internal compliance requirements.
Partner with data analysts, data scientists, and IT operations to build tools and pipelines for data and AI products, including downstream reporting and BI use cases.
Provide technical leadership by mentoring engineers, reviewing designs, and guiding teams through complex technical or production issues.
Apply DevSecOps practices and Agile methodologies, including Jira and Scrum/Kanban, to plan and deliver work.
Monitor and improve application performance, resiliency, and scalability as data volumes grow.