Lead Data Engineer

Position Summary: We are looking for a hands-on Senior Data Engineer with a strong DevOps mindset to design, build, and operate reliable, scalable, and observable data pipelines that power business functions across the enterprise. This is a senior individual-contributor role — you'll independently own the delivery of complex pipelines, uphold engineering standards, deploy via CI/CD, support the operational health of the platform, and mentor junior engineers through reviews and collaboration. Core Skills: Databricks · Python (PySpark) · SQL · Data Pipelines · CI/CD Key Responsibilities: Engineering & Delivery: • Independently design, build, and maintain complex, production-grade data pipelines on Databricks. • Develop efficient ETL/ELT processes with a strong focus on data quality, consistency, and scalability. • Build reusable frameworks for ingestion, transformation, and reconciliation across enterprise source systems. • Apply and help improve engineering standards — pipeline architecture, coding standards, and ETL/ELT best practices. Technical Mentorship: • Mentor junior engineers through code reviews, design reviews, and pair-programming on complex problems. • Share best practices in Databricks/PySpark, coding standards, and engineering discipline. • Contribute to a culture of ownership, automation, and continuous improvement. Operations & DevOps: • Deploy changes through CI/CD and the Change Request (CR) lifecycle, including validation, release management, and ticket closure. • Participate in problem management and root-cause analysis — driving permanent fixes and automation over recurring firefighting. • Support the operational health of business-critical data workloads — monitoring, alerting, and incident response. Collaboration: • Partner with Reporting, Visualization, Platform, and Business teams to expose curated datasets for downstream analytics consumers. • Communicate technical trade-offs, progress, and risks clearly to technical and non-technical stakeholders across geographies. • Document workflows, standards, and runbooks to ensure reproducibility and knowledge continuity. What Success Looks Like (First 6–12 Months): • In your first 6–12 months, you'll independently deliver key data pipelines to a high standard, strengthen data quality and CI/CD practices in your area, reduce recurring incidents through problem management, and become a go-to technical resource for the team. Required Qualifications: • Bachelor's or Master's degree in Computer Science, Information Technology, or equivalent relevant experience. • 6+ years of experience in data engineering. • Strong hands-on background in Databricks, Python (PySpark), and SQL for large-scale data processing. • Proven experience designing and delivering production data pipelines (ETL/ELT) at enterprise scale. • Working knowledge of CI/CD pipelines, Git-based branching strategies, and DevOps practices. • Experience with cloud platforms (AWS preferred) and core data services. • Experience supporting production data pipelines, including monitoring, alerting, and incident response. • Strong communication skills across engineering and business audiences. Preferred Qualifications: • Experience with orchestration frameworks and streaming technologies. • Exposure to Infrastructure-as-Code and modern deployment tooling. • Familiarity with observability tooling for data platforms. • Background in semiconductor manufacturing or large-scale industrial data processing. • Databricks Certified Data Engineer Associate or Professional certification is a plus. Competencies: • Ownership and accountability — end-to-end responsibility for your pipelines, from design to production support. • Problem-solving orientation — bias toward permanent fixes and automation. • Technical depth — leads by example through hands-on engineering and high standards. • Collaboration — works well with Reporting, Platform, and Business teams across geographies. • Clear communication — articulates technical trade-offs to non-technical stakeholders. More information about NXP in India... #LI-7013