Position Summary:
We are expanding our Platform Engineering capability to build, secure, and automate the enterprise Data Platform on cloud and Databricks. This role owns the underlying infrastructure, ingestion frameworks, CI/CD pipelines, orchestration, and observability that enable Data Engineers and Analytics teams to operate at scale. The ideal candidate combines strong platform engineering fundamentals with hands-on DevOps skills across data replication, job scheduling, deployment automation, and cloud operations.
Key Responsibilities:
Infrastructure & Platform Engineering
Deploy and maintain Databricks workspaces and cloud infrastructure using Infrastructure-as-Code.
Manage platform upgrades, patching, current flow setup, and environment refresh support.
Support enterprise data replication (HVR) and file-based ingestion patterns from operational systems into the data platform.
Orchestration & Job Scheduling
Provide monitoring, recovery, and operational support for enterprise job scheduling and orchestration.
Configure job dependencies and coordinate with source teams on long-running workloads.
CI/CD & Deployment Automation
Design and maintain GitLab CI/CD pipelines for data and platform projects with automated deployment workflows.
Standardize deployment strategies using reusable templates and Databricks-native deployment tooling.
Implement branching strategies, code review policies, and environment promotion rules.
Support the Change Request (CR) deployment lifecycle, including validation and ticket closure.
Monitoring, Reliability & Support
Configure monitoring, alerting, and logging to ensure platform stability.
Serve as an escalation point for platform-related incidents and vendor coordination.
Support year-end activities and compliance reporting requirements.
What Success Looks Like (First 6–12 Months):
In your first 6–12 months, you'll stabilize CI/CD and monitoring for key platform flows, automate recurring operational tasks, and streamline the change-requ