Data & ML Devops Engineer

Responsibilities:

• Provide

  L2/L3 support

  for machine learning operations and Snowflake platform workflows during India business hours.
• Monitor and troubleshoot issues related to

  ML model deployment

  ,

  batch/real-time inference pipelines

  , and

  data workflows

  .
• Support

  Snowflake DevOps operations

  , including warehouse monitoring, job scheduling, query performance tuning, and access control.
• Ensure reliability of data ingestion and transformation pipelines built on

  Matillion

  ,

  Fivetran

  , and

  Snowpipe

  .
• Support and enhance

  CI/CD pipelines

  for ML model packaging, testing, deployment, and rollback.
• Collaborate with Data Scientists, Engineers, and Cloud Platform teams to resolve incidents and improve system reliability.
• Use

  ServiceNow

  and

  Jira

  to manage and track support tickets, ensure SLA compliance, and provide timely resolution or escalation.
• Proactively build monitoring tools, runbooks, and automation scripts to improve incident response time and reduce manual effort.
• Maintain logs, dashboards, and alerts for both ML and data infrastructure using appropriate monitoring tools (e.g., CloudWatch, Prometheus, Snowflake monitoring).
• Ensure compliance with internal security, data privacy, and responsible AI standards.

Qualifications:

• Bachelors degree in Computer Science, Engineering, or a related technical field.
• 3–6 years of experience in

  ML Ops

  ,

  DevOps

  , or

  Data Platform support

  roles.
• Strong experience with

  Snowflake

  , including RBAC, warehouse tuning, streams/tasks, monitoring, and query troubleshooting.
• Hands-on support experience with

  ML platforms

  like

  DataRobot

  ,

  RapidCanvas

  ,

  SageMaker

  , or custom-built frameworks.
• Experience with

  CI/CD tools

  (GitHub Actions, Azure DevOps, Jenkins) and scripting (Python, Bash).
• Exposure to data integration tools:

  Matillion

  ,

  Fivetran

  , and

  Snowpipe

  .
• Understanding of

  model monitoring

  , version control, and retraining workflows.
• Experience with

  incident response processes

  , root cause analysis, and preventative remediation.
• Familiarity with

  data governance

  , compliance, and audit capabilities in Snowflake.
• Strong SQL skills and experience automating Snowflake tasks and managing workflows.
• Excellent communication and documentation skills, with the ability to coordinate with global teams.