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 workplace 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...

📌 Lead Data Platform Engineer (Bengaluru)
🏢 NXP Semiconductors
📍 Bengaluru