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...](https://www.nxp.com/company/about-nxp/worldwide-locations/india:INDIA) #LI-29f4