Data & Analytics DevOps Engineer
- Build and maintain Azure DevOps CI/CD pipelines for Data Engineering, dbt, Snowflake, and analytics workloads.
- Support deployment and promotion of data models, database objects, pipelines, and configurations across development, test, and production environments.
- Provide day-to-day operational support for Snowflake, including environment configuration, maintenance, monitoring, performance, access, and troubleshooting.
- Support Fivetran connectors and data integration processes, including monitoring failures, schema changes, and data movement.
- Support DevOps and operational processes for Power BI, including deployment pipelines, workspaces, semantic models, gateways, connections, and refresh monitoring.
- Automate recurring platform administration, deployment, and support activities using scripting, APIs, and workflow automation.
- Support data catalog administration, security, governance, and platform connectivity.
- Assist with integrations to AI and automation technologies such as n8n, Snowflake MCP, and related tools.
- Maintain deployment standards, operational documentation, and support runbooks.
- Partner with Data Engineering, BI, Infrastructure, Security, and Data Science teams to improve platform reliability and operational efficiency.
- Assist with Data Science and ML deployment processes as those capabilities mature.
Qualifications:
- 3–5 years of experience in DevOps, Data Engineering, platform engineering, analytics engineering, or a related role.
- Hands-on experience with Azure DevOps, Git, CI/CD pipelines, and release processes.
- Working knowledge of Snowflake or a comparable cloud data platform.
- Experience with SQL and deploying data or analytics solutions across multiple environments.
- Familiarity with dbt or similar data transformation and modeling technologies.
- Experience with scripting or automation using Python, PowerShell, SQL, APIs, or similar tools.
- Strong troubleshooting and problem-solving skills.
- Ability to work effectively across Data Engineering, BI, and infrastructure teams.