Join the elite engineering team at a leading global media organization, where technology meets world-class content. We are seeking a highly motivated and skilled Senior Data Engineer to lead the architecture, deployment, and operation of our next-generation, data-driven platforms. You will be instrumental in bridging the gap between Data Science and Operations, ensuring our datasets, machine learning models and core services are deployed reliably, scalably, and securely across the cloud.

This is a high-impact role requiring deep expertise in core engineering, data architecture, and the full Machine Learning lifecycle in a production environment.

• Data Pipeline Design & Orchestration: Design, build, and maintain robust data ingestion and transformation pipelines, leveraging modern orchestration tools to ensure reliable data flow for ML models.

• Core Development: Write clean, efficient, and well-tested code in Python for automation scripts, infrastructure tooling, and glue services connecting cloud components.

• API and Service Deployment: Design, develop, and deploy high-performance Python APIs (FastAPI/Flask) to serve machine learning predictions and core application logic.

• MLOps Pipeline Ownership: Design and manage end-to-end pipelines for continuous training, deployment, and versioning of high-impact ML models (e.g., recommendation systems).

• Infrastructure Management: Architect and maintain scalable, fault-tolerant infrastructure using Kubernetes (GKE) across Google Cloud Platform (GCP).

• Collaboration & Mentorship: Work closely with data scientists and software engineers; provide technical guidance and mentorship to junior team members.

Must-Have (Engineering Excellence)

• Experience: 5+ years of professional experience in Data Engineering, Software Engineering, or Cloud Engineering.

• Python Mastery: Deep expertise in Python for application development, data and automation

• Backend Development: Proven experience building and deploying production-ready APIs and backend services using frameworks like FastAPI, Flask, or Django.

• Data Architecture: Strong proficiency in SQL and experience designing/optimizing schemas for relational/NoSQL databases and data warehouses (e.g., BigQuery, Cloud SQL).

• Orchestration: Hands-on experience with data pipeline and workflow orchestration tools such as Dagster or Airflow.

• Cloud Fundamentals: Extensive experience designing and managing scalable services within the Google Cloud Platform (GCP) ecosystem (BigQuery, Pub/Sub, Vertex AI, Compute Engine).

• Containerization: Expert-level knowledge of Docker and Kubernetes, including hands-on experience with package management (Helm).

Nice-to-Have (DevOps & MLOps)

• Infrastructure as Code (IaC): Experience with Terraform, Crossplane, or similar tools to drive automated infrastructure provisioning.

• CI/CD Implementation: Experience configuring automated deployment and testing pipelines using GitHub Actions.

• Observability: Familiarity with monitoring, logging, and alerting solutions (Prometheus, Grafana, Cloud Logging) to diagnose production issues.

• Security: Understanding of network architecture, security principles, and media industry compliance standards.

• ML Lifecycle: Experience specifically focusing on MLOps in a production environment (model monitoring, drift detection, and automated retraining).

What We Offer

• Competitive salary and comprehensive benefits package.
• The opportunity to work on cutting-edge machine learning and streaming infrastructure that impacts 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 reasonable estimate, if hired in New York City, is $155,000 - $170,000. 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.