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.
More information about NXP in India...
#LI-29f4
