Lead Data Platform Engineer

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