Analytics Data Engineer – Contract
EEOC
AWSHadoopPythonSparkSQL
Senior Data Engineer
Hearst Health
full-time
Posted on:
Location Type: Hybrid
Location: New York City • New York • 🇺🇸 United States
Visit company websiteSalary
💰 $150,000 - $165,000 per year
Job Level
Senior
Tech Stack
AirflowBigQueryCloudDjangoDockerFlaskGoogle Cloud PlatformKubernetesNoSQLPythonSQLTerraform
About the role
- 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.
- Data Pipeline Design & Orchestration: Design, build, and maintain robust data ingestion and transformation pipelines.
- Kubernetes and Cloud Architecture: Architect, deploy, and maintain highly scalable, fault-tolerant infrastructure using Kubernetes 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.
- CI/CD Implementation: Configure and manage automated deployment and testing pipelines using GitHub Actions and other integrated tools.
- Core Development: Write clean, efficient, and well-tested code in Python for automation scripts and infrastructure tooling.
- API and Service Deployment: Design, develop, and deploy robust, high-performance Python APIs to serve machine learning predictions.
- Monitoring and Observability: Implement comprehensive monitoring, logging, and alerting solutions.
- Security and Compliance: Ensure platform integrity by implementing security best practices.
- Collaboration and Mentorship: Work closely with data scientists, software engineers, and product managers; provide technical guidance and mentorship.
Requirements
- 5+ years of professional experience in DevOps, Cloud Engineering, or a related field.
- 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.
- 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).
- Hands-on experience with package management (e.g., Helm Charts) and Kubernetes-native Infrastructure as Code tools (Crossplane).
- Extensive hands-on experience designing and managing scalable services within the Google Cloud Platform (GCP) ecosystem.
- Fluency in version control and collaboration workflows using GitHub.
- Strong understanding of network architecture, security principles, and large-scale data processing technologies.
- Excellent communication and problem-solving skills.
Benefits
- Competitive salary and comprehensive benefits package.
- Health insurance
- Dental insurance
- Vision insurance
- Disability insurance
- Life insurance
- 401(k)
- Paid holidays
- Paid time off
- Employee assistance programs
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
MLOpsPythonSQLAPI developmentData pipeline designContainerizationInfrastructure as CodeCI/CDMonitoring and observabilitySecurity best practices
Soft skills
CollaborationMentorshipCommunicationProblem-solving
