Join a leading financial organization and take a significant part in shaping the future of Data, AI, and enterprise Data Governance. As a DevOps Engineer within a strategic Data & AI division, you will lead the implementation and operation of the organization's Data Governance platform, building scalable infrastructure, automation processes, and integrations that enable trusted, governed, and discoverable data across the enterprise. You will work closely with Data Engineers, Platform Engineers, Architects, DevOps teams, and Governance stakeholders while supporting modern cloud environments and large-scale enterprise data platforms.
What You'll Do:
- Lead the implementation, deployment, and operation of the OpenMetadata platform across Development, Test, and Production environments
- Build, configure, and maintain cloud-native infrastructure supporting the organization's Data Governance platform
- Develop automation processes for Metadata Ingestion, Data Lineage, and Data Quality workflows
- Design and develop custom integrations and extensions using Python and APIs
- Integrate the platform with enterprise Data Warehouses, Data Lakes, data pipelines, and additional data sources
- Build and maintain CI/CD pipelines for platform deployment and ongoing development
- Manage containerized environments using Docker and Kubernetes
- Monitor platform performance, troubleshoot issues, and optimize system reliability and scalability
- Implement security best practices and support compliance requirements within a highly regulated environment
- Collaborate closely with Data Engineers, Architects, DevOps teams, and Data Governance stakeholders to deliver enterprise-wide data capabilities
Qualifications:
- 3+ years of experience in DevOps, Data Engineering, or Platform Engineering roles – Must
- Strong hands-on experience with Python and SQL - Must
- Experience deploying and operating open-source platforms - Must
- Experience working with Docker and Kubernetes - Must
- Experience designing and maintaining CI/CD pipelines - Must
- Strong understanding of Data Architecture, including Data Warehouses (DWH), Data Lakes, and data ingestion pipelines - Must
- Experience working with cloud platforms such as AWS, Azure, or GCP - Must
- Experience working with APIs and system integrations - Must
- Experience with OpenMetadata or similar Data Catalog platforms -Advantage
- Experience implementing Metadata Ingestion and Data Lineage processes -Advantage
- Experience with Data Quality tools such as Great Expectations or Soda -Advantage
- Familiarity with Airflow or other workflow orchestration tools -Advantage
- Experience working in regulated environments, such as banking, financial services, or insurance -Advantage
- Familiarity with Information Security and Data Governance principles and best practices -Advantage
