Key Responsibilities :

- Manage and support cloud and data platforms, including AWS, Databricks, and Snowflake, across development and production environments.

- Handle infrastructure configuration, platform administration, access management, deployment, integration, and operational troubleshooting.

- Design, maintain, and optimize GitLab CI/CD pipelines covering build, test, release, approvals, quality gates, and deployment automation.

- Manage release automation, environment configurations, deployment strategies, and production readiness activities.

- Troubleshoot platform, application, pipeline, and deployment-related issues by analysing logs, errors, and system behaviour.

- Support Kafka-based integrations and troubleshoot connectivity, topics, partitions, producers, consumers, and offsets.

- Monitor platform health, identify operational issues, and ensure reliable availability of cloud and data engineering workloads.

- Implement and support security practices, including access governance, secrets management, vulnerability scanning, and audit controls.

- Work with engineering teams to improve automation, deployment efficiency, platform reliability, and operational processes.

- Participate in incident management, root-cause analysis, and remediation activities.

- Maintain technical documentation, operational procedures, and deployment guidelines.

Skillset :

- AWS, Databricks and Snowflake platform engineering, including infrastructure configuration, access management, deployment, integration, operational support and troubleshooting.

- GitLab DevOps & CI/CD pipelines, including build/test/release workflows, approvals, quality gates, deployment automation and artefact management.

- DevOps engineering fundamentals, including release automation, environment management, deployment strategies, infrastructure/platform support, production troubleshooting and operational readiness.

- Fundamentals of at least one programming or scripting language, with the ability to understand code, interpret logs and errors, troubleshoot applications and pipelines, support automation, and collaborate with engineering teams on code-level diagnosis.

- Kafka fundamentals, including topics, partitions, producers/consumers, offsets, connectivity and operational troubleshooting.

- Experience supporting data engineering and cloud platform workloads across development and production environments.

Highly Valued Skills :

- Experience with AWS services such as S3, IAM and KMS.

- Experience with Databricks administration and engineering.

- Experience with Snowflake, including databases, schemas, roles/RBAC.

- Experience with Oracle from an operational perspective.

- Strong understanding of observability and monitoring, including AppDynamics (AppD).

- Good working knowledge of JIRA, GitLab and Agile delivery practices.

- Understanding of API engineering concepts, including REST, authentication/security patterns.

- Exposure to security and controls, including vulnerability scanning, secrets management.

- Exposure to automation and Infrastructure-as-Code principles.

- Understanding of production support and incident management.