Discovery and Requirements Gathering:

• DevOps Maturity Assessment: Evaluated CI/CD tooling, version control, and deployment strategies.

• Toolchain Audit: Identified redundant or outdated components across engineering teams.

• Data Flow Mapping: Analyzed sources, storage layers, and transformation pipelines.

• Stakeholder Alignment: Engaged product, DevOps, data engineering, and QA leads to align goals.

DevOps Automation & CI/CD Standardization:

• Standardized CI/CD pipelines using GitHub Actions, GitLab CI, and Jenkins pipelines-as-code.

• Integrated secrets management with Vault and parameterized build environments.

• Enforced peer-reviewed code policies and automated rollback mechanisms.

Infrastructure as Code (IaC):

• Implemented Terraform for reproducible, multi-cloud infrastructure provisioning.

• Created centralized module libraries with policy enforcement via Sentinel and OPA.

• Consolidated tools around Git, Docker, Kubernetes and Helm for consistency.

• Defined tool usage standards and governance through Confluence-based runbooks and diagrams.

Data Pipeline Modernization:

• Replaced ad-hoc ETL jobs with managed orchestration (e.g., Apache Airflow).

• Introduced schema versioning and data contracts to enforce quality and traceability.

• Integrated data lineage visualization using tools like OpenMetadata and Amundsen.

Collaboration and Enablement:

• Built internal DevOps and DataOps enablement hubs with self-service templates and documentation.

• Conducted live workshops on GitOps, IaC, and data pipeline best practices.

• Launched continuous improvement sprints to evolve pipeline maturity.