DevOps Engineer

We are seeking a hybrid Dev Ops + Data Engineering profile, with a stronger emphasis on Dev Ops capabilities. The role owner will be required to modify & manage ETL pipelines as part of platform operations. The role owner should have hands on Dev Ops experience along with good understanding of data pipelines.

• Modify and manage data pipelines in Dev Ops setup.
• Good understating of CI/CD pipelines.

• Upgrade and maintain third-party components such as ingress controllers, service meshes, monitoring agents, infrastructure libraries, and cloud-native tools.
• Apply the latest versions and security patches to ensure compliance, stability, and performance.
• Update and enhance IaC scripts to support version upgrades across development, QA, and production environments.
• Validate changes through sandbox testing before deployment to production.

• Ensure upgraded components remain compatible with dependent services and applications.
• Identify and mitigate potential breaking changes or dependency conflicts.

• Implement necessary code changes in supported languages (e.g., Python) to accommodate new versions or configuration requirements.
• Address minor and moderate changes required for compatibility with upgraded components.
• Update existing unit tests in response to the application code changes.

• Apply immediate fixes for vulnerabilities.
• Maintain adherence to organizational security and governance guidelines.

• Create and execute test strategies for validating the upgrades.
• Execute existing unit tests and manual test cases post-upgrade.
• Conduct functional testing of impacted applications to ensure end-to-end stability.
• Validate application behavior after code changes and infrastructure updates.

• Provide weekly status reports detailing software versions, security posture, upgrade activities, and testing outcomes.
• Participate in regular reviews and acceptance processes.

• Terraform.
• Platform upgrades and maintenance.
• QA exposure – integration & platform testing.
• Deep understanding of cloud data services (AWS) and migration strategies.
• Strong proficiency in ETL/ELT pipelines and framework development using Python. Development may not be needed but understanding is required.
• Modifying & monitoring data pipelines for batch and real-time processing.
• Exceptional communication skills for engaging executives and non-technical stakeholders.
• Knowledge of containerization (Docker, Kubernetes) and orchestration for data workloads.

• Certifications in cloud platforms (AWS) and data engineering.
• Experience with advanced analytics and machine learning pipelines.
• Prior consulting experience or leading large-scale data transformation programs.
• Knowledge of data extraction from SAP OData Services.
• Experience with multiple relational and No
  
  SQL databases (Must have - Redshift, RDS and Athena).
• Experience with BI tools integration with enterprise data platforms.

• Bachelor’s degree in computer science, engineering, or related field (master's degree is a plus).
• Demonstrated continued learning through one or more technical certifications or related methods.
• At least 10+ years of relevant experience; two years may be substituted for a master’s degree.