Senior Platform Engineer (Data Platform / DevOps)

Summary

Build, secure, and automate an enterprise Data Platform on cloud and Databricks, owning infrastructure, CI/CD pipelines, orchestration, and observability that enable data and analytics teams to operate at scale. Core stack: Databricks, AWS, GitLab CI/CD, Python, Bash, Infrastructure-as-Code.

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, new 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-request and deployment lifecycle.

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Information Technology, or equivalent relevant experience.
  • 6+ years of industry experience in Data Engineering, Cloud Infrastructure, or DevOps.
  • Hands-on experience with CI/CD tooling (GitLab preferred) — pipeline authoring, release management, and secrets management.
  • Strong grounding in cloud platforms (AWS preferred) for data workloads.
  • Working knowledge of Databricks platform administration.
  • Experience with monitoring and observability tools, proactive alerting, and incident triage.
  • Proficient in Python and Bash/Shell scripting for automation.

Preferred Qualifications:

  • Experience with enterprise data replication tools (e.g. HVR).
  • Advanced Infrastructure-as-Code skills.
  • Familiarity with enterprise job orchestration platforms (e.g. Autopilot).
  • Exposure to Databricks Serverless Compute and Workflow orchestration.
  • Cloud Solutions Architect or Databricks certifications are a plus.

Competencies:

  • Reliability-first mindset — focus on stability, automation, and self-healing systems.
  • Strong sense of ownership across the platform lifecycle — build, run, and evolve.
  • Effective vendor coordination and cross-team collaboration.
  • Clear documentation and knowledge-sharing habits.


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