Do you enjoy building robust data pipelines and laying the foundation for impactful AI and reporting solutions? Join NXP’s R&D IT team and help shape the future of semiconductor innovation. As a Data Engineer, you’ll work at the intersection of data, AI, and cloud technologies, collaborating with global teams to deliver scalable, reliable, and high-quality data solutions. We are looking for a versatile data professional who can navigate multiple data paradigms – graph-based, relational and we-driven – and design robust solutions for transforming and integrating these structures.
Role and responsibilities
You’ll be part of the Unified Data Platform team, responsible for developing and maintaining data pipelines that support enterprise reporting and AI use cases across NXP.
Key responsibilities include:

• Refactor and build reusable data pipelines in AWS and Databricks.
• Collaborate with business analysts, data scientists, architects, developers, and business stakeholders to deliver fit-for-purpose solutions.
• Design and develop cloud-based solutions for data lakes, data warehouses, ETL processes and backend services for structured, and unstructured data.
• Participate in code reviews and documentation efforts.
• Optimize pipelines for cost, scalability, reliability and security
• Implement rigorous testing and monitoring protocols.
• Resolve performance bottlenecks and optimize workloads.
• Stay current with data engineering trends and apply them where relevant.
• Mentor other data engineers and contribute to competence development.
• Education and experience
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• 10+ years of experience in data engineering, data analytics and backend services.
• Hands-on experience with AWS Cloud and Databricks
• Proficiency across multiple execution and query paradigms, including:
• Event-driven and orchestration workflows for serverless computing (AWS Lambda, Step Functions)
  • General-purpose and scripting languages for automation and data processing (Python, Bash, Make)
  • Query languages for structured and semantic data (SQL, SPARQL).
• Solid understanding of multiple data paradigms, including
  • Relational data for structured storage and analytics (AWS Redshift)
  • Key-value and document-oriented models for high-performance transactional workloads (DynamoDB)
  • Object storage for semi-structured data and large-scale lakes (AWS S/3)
  • Graph-based data models for relationship-driven queries and semantic structures (AWS Neptune)
• GIT and CI/CD experience required; GitLab preferred
• Infrastructure as Code experience required; AWS CDK preferred
• Experience with Gitlab for Version Management, CI/CD and CDK for Infra as Code.

Skills:

Working at the cutting edge of tech, you’ll always have new challenges and new problems to solve – and working together is the only way to do that. You won’t work in a silo. Instead, you’ll be part of a creative, dynamic work environment where you’ll collaborate with supportive colleagues. There is always space for creative and unique points of view. You’ll have the flexibility and trust to choose how best to tackle tasks and solve problems.

To thrive in this job, you’ll need the following skills:

• Passion for data engineering and solving real-world problems.
• Customer-centric mindset and value-driven approach.
• Strong analytical and problem-solving capabilities.
• Excellent collaboration and communication skills.
• Knowledge of data architecture techniques and data modeling concepts.
• Exceptional mentorship abilities
• Familiarity with agile and scrum methodologies.
• Proactive attitude toward continuous improvement.
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