Automate common ServiceNow request workflows related to data platform access, onboarding, approvals, fulfilment, and operational requests.
Build or enhance self-service applications that integrate with ServiceNow and raise requests on behalf of users.
Develop automated backup scripts and scheduled jobs for platform components such as Databricks Unity Catalog/metastore, Dremio metadata, configuration, ADLS objects, and other platform assets.
Build tested restore scripts and runbooks for Dremio metadata, Databricks views, catalog objects, platform configurations, and other recoverable assets.
Support ADLS disaster recovery planning, backup validation, failover readiness, and recovery testing.
Responsible for both development and strong expertise to debug and fix any post production issues
Create reusable scripts, notebooks, templates, and automation patterns for Databricks workloads, views, jobs, and pipelines.
Work with platform users to review and optimize Databricks pipelines, improve performance, reduce cost, and promote reusable engineering patterns.
Develop and maintain Terraform modules for Azure/GCP infrastructure used by the data platform.
Build and maintain CI/CD pipelines using GitHub Actions/GitHub runners for deploying infrastructure, scripts, configurations, and platform automation.
Help reduce repetitive operational work by identifying automation opportunities and implementing robust, reusable solutions.
Own automation tasks end-to-end, from requirements gathering through development, testing, deployment, and support handover.
Leads: Role is 70% of time in Design, Architect, Coding and 30% of time in team mentoring, guidance, coordination
Required Technical Skills:
Strong scripting experience using Python, Bash, PowerShell, or similar languages.
Ability to build production-ready automation scripts.
Experience integrating with ServiceNow APIs, automating ticket creation, request fulfilment, approvals, and workflow-driven processes.
Good working knowledge of Databricks workspaces, jobs, notebooks, clusters, SQL warehouses, Unity Catalog/metastore concepts, views, and pipeline optimization.
Responsible for both development and strong expertise to debug and fix any post production issues for their developed code
Experience or willingness to learn Dremio administration, metadata backup/restore, source configuration, reflections, spaces, folders, and operational support.
Experience with Azure Data Lake Storage, storage accounts, RBAC, managed identities, private networking, and disaster recovery concepts.
Ability to design, automate, test, and document backup and restore processes for data platform metadata, configurations, and platform assets.
Strong Terraform knowledge, including module development, state management, variables, providers, workspaces, and reusable infrastructure patterns.
Strong Azure experience required.
Ability to work with REST APIs, authentication mechanisms, secrets, tokens, and service principals.