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What You'll Do
- Engineering & Delivery: Design, build, and maintain production-grade data pipelines on Databricks.
- Develop efficient ETL/ELT processes with a strong focus on data quality, consistency, and scalability.
- Contribute to reusable frameworks for ingestion, transformation, and reconciliation across enterprise source systems.
- Apply established engineering standards — pipeline architecture, coding standards, and ETL/ELT best practices.
- Operations & DevOps: Deploy changes through CI/CD and the Change Request (CR) lifecycle, including validation and ticket closure.
- Participate in problem management and root-cause analysis, helping drive 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 deliver curated datasets for downstream analytics consumers.
- Communicate progress, issues, and technical details clearly to engineering peers and stakeholders.
- 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 assigned data pipelines to a high standard, become comfortable with CI/CD and operational practices, and contribute to improving data quality and reducing recurring incidents — with guidance from senior engineers. Required Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, or equivalent relevant experience. 4+ years of experience in data engineering.
- Hands-on experience with Databricks, Python (PySpark), and SQL for data processing and transformation.
- Experience designing and delivering production data pipelines (ETL/ELT).
- Working knowledge of CI/CD pipelines and Git-based branching strategies.
- Familiarity with cloud platforms (AWS preferred) and core data services.
- Experience supporting production data pipelines, including monitoring, alerting, and incident response.
- Good communication skills across engineering and business audiences.
Nice to Have
- Exposure to orchestration frameworks and streaming technologies.
- Familiarity with Infrastructure-as-Code and modern deployment tooling.
- Awareness of observability tooling for data platforms.
- Background in semiconductor manufacturing or large-scale industrial data processing.
- Databricks Certified Data Engineer Associate certification is a plus.
- Competencies: Ownership mindset — accountable for the quality of your pipelines, from build to production support.
- Problem-solving orientation — bias toward permanent fixes and automation.
- Growing technical depth — strong hands-on engineering and attention to quality.
- Collaboration — works well with Reporting, Platform, and Business teams across geographies.
- Clear communication — able to explain technical details to peers and stakeholders.
- More information about NXP in India... #LI-7013
Tools & Skills
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Sourced directly from NXP Semiconductors’s career page
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Specialisation
Open roles at NXP Semiconductors
779 positions
Job ID
/job/Bangalore/Senior-Data-Engineer_R-10066226
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