Senior IT Data Engineer R&D IT

Are you ready to join the future of innovation at NXP As a data engineer you will directly impact the cost efficiency and speed of NXPs New Product Introductions as you will be responsible for the quality of the data and business insights that enable correct R&D business decisions. Together with your data engineering team and the R&D data scientists you shape the future of the R&D data analytics platform. Your solutions delight R&D business with a topnotch self-service fully automated cloud-based data platform. What you will do as a Data Engineer at NXPAs part of the data engineering team you will help shape and evolve the R&D data analytics platform. You will work closely with colleagues to explore new ideas innovate on existing capabilities and drive the platform forward through collaboration and technical key responsibilitiesCross Functional Collaboration & Enablement: Partner with project managers resource managers IT teams data scientists and analysts to gather requirements define project scope and deliver reliable model ready datasets. Removing data pipeline friction and ensuring strong alignment with business build and maintain ETL pipelines that ingest and transform data into a cloud-based R&D data reusable data models and libraries that streamline common analytics and ETL use and uphold data quality through validation monitoring and anomaly detection security and compliance by embedding RBAC lineage auditing and regulatory standards into ETL pipelines for performance scalability and cost deployments and operations using CI/CD Infrastructure as Code and ETL and troubleshoot production pipelines resolving data or platform issues and improving reliability over you bringYou can describe yourself as follows: Education & ExperienceEducation: Masters degree (or equivalent practical experience) in Data Engineering Software Engineering Computer Science or related technical field. Experience: 7 years of professional data engineering experience working with Big Data within an enterprise IT infrastructure environment. AWS Data Lake Experience: Hands on experience with AWS-native data lake services including AWS Glue S3 Athena and Lake Formation covering cataloging governance ETL orchestration and secure data access Expertise: Extensive hands-on hands-on experience designing and implementing ETL pipelines in Databricks including proven experience migrating existing cloud-based data lakes and ETL workflows to the Databricks Lake Expertise: Strong experience working with Delta Lake including designing Delta tables optimizing performance and managing schema evolution and versioned SkillsCloud & Automation: Strong experience with cloud-native engineering (Azure/AWS) Infrastructure-as-Code CI/CD and DevOps/MLOps best practices. Hands-on experience with AWS CDK Ansible and GitLab CI is a big : Advanced proficiency in Python and SQL with the ability to build robust maintainable and reusable code Quality & Governance: Strong command of observability lineage data quality frameworks metadata management and secure data access Optimization: Expertise in cluster/job tuning job orchestration storage optimization and cost management in large data lake AttributesCustomer & Stakeholder Focus: Strong communicator who can translate technical concepts into business value and collaborate effectively across data science architecture and wider R& Problem-Solving: Comfortable owning technical challenges and designing long-term scalable Mindset: A natural collaborator who contributes to an open supportive working Ways of Working: Familiarity with Agile and Scrum methodologies including iterative delivery sprint planning backlog refinement and cross-functional collaboration.

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