Senior Data Engineer

Senior Data Engineer Role Summary

Join the engineering team helping to drive data innovation across Hearst's global portfolio of consumer media businesses.. 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 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 automation, cloud infrastructure, and the full Machine Learning lifecycle in a production environment.

Key Responsibilities

• MLOps Pipeline Ownership: Design, implement, and manage end-to-end MLOps pipelines for the continuous training, deployment, monitoring, and versioning of high-impact ML models (e.g., recommendation systems, content intelligence).
• Data Pipeline Design & Orchestration: Design, build, and maintain robust data ingestion and transformation pipelines, leveraging modern orchestration tools (such as Dagster or Airflow) to ensure reliable data flow for ML models.
• Kubernetes and Cloud Architecture: Architect, deploy, and maintain highly scalable, fault-tolerant infrastructure using Kubernetes (GKE) across Google Cloud Platform (GCP).
• DevOps and Automation: Drive DevOps culture and best practices, focusing on Infrastructure as Code (IaC) using Terraform or similar tools, and establishing robust CI/CD workflows.
• CI/CD Implementation: Configure and manage automated deployment and testing pipelines using GitHub Actions and other integrated tools, ensuring fast and reliable code delivery.
• 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 robust, high-performance Python APIs (using frameworks like FastAPI or Flask) to serve machine learning predictions and core application logic in a production environment.
• Monitoring and Observability: Implement comprehensive monitoring, logging, and alerting solutions (e.g., Prometheus, Grafana, Cloud Logging) to maintain high availability and quickly diagnose production issues.
• Security and Compliance: Ensure platform integrity by implementing security best practices, access controls, and adhering to media industry compliance standards.
• Collaboration and Mentorship: Work closely with data scientists, software engineers, and product managers; provide technical guidance and mentorship to junior team members.

Required Qualifications

• 5+ years of professional experience in DevOps, Cloud Engineering, or a related field, with at least 2 years specifically focusing on MLOps in a production environment.
• Deep expertise in Python for development, scripting, and automation.
• Proven experience building and deploying production-ready APIs and backend services using Python frameworks (e.g., FastAPI, Flask, or Django).
• Strong proficiency in SQL and experience designing and optimizing schemas for relational/NoSQL databases and data warehouses (e.g., BigQuery, Cloud SQL).
• Experience with data pipeline and workflow orchestration tools (Dagster, Airflow).
• Expert-level knowledge of containerization technologies (Docker) and orchestration platforms (Kubernetes), including hands-on experience with package management (e.g., Helm Charts) and Kubernetes-native Infrastructure as Code tools (Crossplane). Experience with Google Kubernetes Engine (GKE) is highly desirable.
• Extensive hands-on experience designing and managing scalable services within the Google Cloud Platform (GCP) ecosystem (e.g., Compute Engine, Cloud Storage, BigQuery, Pub/Sub, Vertex AI).
• Fluency in version control and collaboration workflows using GitHub (branching strategies, pull requests, code reviews).
• Strong understanding of network architecture, security principles, and large-scale data processing technologies.
• Excellent communication and problem-solving skills.

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 $150,000 - $165,000. 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.