Senior Data Engineer

Senior Data Engineer at Hearst

Join the engineering team helping to drive data innovation across Hearst’s global portfolio of consumer media businesses. This high-impact role requires deep expertise in automation, cloud infrastructure, and the full Machine Learning lifecycle in a production environment.

• Design, implement, and manage end-to-end MLOps pipelines for continuous training, deployment, monitoring, and versioning of high-impact ML models.
• Design, build, and maintain robust data ingestion and transformation pipelines using orchestration tools such as Dagster or Airflow.
• Architect, deploy, and maintain highly scalable, fault‑tolerant infrastructure using Kubernetes (GKE) on Google Cloud Platform.
• Drive Dev Ops best practices, focusing on Infrastructure as Code with Terraform and establishing CI/CD workflows.
• Configure automated deployment and testing pipelines using Git Hub Actions.
• Write clean, efficient, well‑tested Python code for automation scripts, infrastructure tooling, and glue services.
• Develop and deploy high‑performance Python APIs (FastAPI or Flask) to serve ML predictions and core application logic.
• Implement monitoring, logging, and alerting solutions (Prometheus, Grafana, Cloud Logging).
• Ensure security best practices, access controls, and compliance with media industry standards.
• Collaborate with data scientists, software engineers, and product managers; mentor junior team members.

• 5+ years of professional experience in Dev Ops, Cloud Engineering, or a related field, with at least 2 years focused on MLOps in production.
• Deep expertise in Python for development, scripting, and automation.
• Proven experience building and deploying production‑ready APIs and backend services using Python frameworks (FastAPI, Flask, or Django).
• Strong proficiency in SQL and experience designing and optimizing schemas for relational/No
  
  SQL databases and data warehouses.
• Experience with data pipeline and workflow orchestration tools (ster, Airflow).
• Expert‑level knowledge of containerization (Docker) and orchestration (Kubernetes), package management (Helm), and Kubernetes‑native IaC (Crossplane). Experience with GKE is highly desirable.
• Extensive hands‑on experience designing and managing scalable services within Google Cloud Platform (Compute Engine, Cloud Storage, Big Query, Pub/Sub, Vertex AI).
• Fluency in Git Hub collaboration workflows (branching, pull requests, code reviews).
• Strong understanding of network architecture, security principles, and large‑scale data processing technologies.
• Excellent communication and problem‑solving skills.

• Competitive salary and comprehensive benefits package.
• Opportunity to work on cutting‑edge machine learning and streaming infrastructure impacting millions of users globally.
• A collaborative and innovative culture within a financially stable and growth‑oriented media leader.

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 estimate is $150,000 – $165,000. For hires outside New York City, the range will be aligned to the location. Final salary will be determined by skills and experience.

Hearst provides a competitive benefits package, including medical, dental, vision, disability, life insurance, 401(k), paid holidays, paid time off, employee assistance programs, and more.

Hearst is a leading global, diversified information, services, and media company dedicated to innovating, informing audiences, and leading with purpose, integrity, and a culture of care. Our portfolio includes more than 360 businesses worldwide, including television stations, daily newspapers, magazine editions, cable networks (A&E, HISTORY, Lifetime, ESPN), and leading business‑to‑business companies such as Fitch Group, Hearst Health, and Hearst Transportation.

We are an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, national origin, sex or gender, sexual orientation, gender identity or expression, age, disability, military or veteran status, or any other status protected by federal, state, or local law. We provide reasonable accommodations to applicants and employees consistent with applicable law.