We are seeking a Hybrid DevOps + Data Engineering profile, with a stronger emphasis on DevOps capabilities. The role owner will be required to modify & manage ETL pipelines as part of platform operations. The role owner should have hands on DevOps experience along with good understanding of data pipelines.
Key Result Areas and Activities:DevOps requirements:- Modify and manage data pipelines in DevOps 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 NoSQL 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.
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