Principal Graph Data Engineer- R&D IT
NXP Semiconductors · Posted Oct 8
High-performance mixed-signal and standard semiconductor products for automotive, industrial, and mobile applications
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About the role
The R&D IT data engineering team at NXP builds and evolves the R&D data analytics platform that enables correct R&D business decisions, with a focus on data quality and business insights for New Product Introductions. The platform is a cloud-based, self-service and fully automated data and analytics stack spanning ETL/ELT, data lakes and Lakehouse ecosystems. This role owns graph data engineering: designing graph-to-relational data models, ontologies and semantic structures, and building scalable pipelines that make graph data accessible for analytics, reporting and AI use cases across the enterprise.
What you will do
- Partner with business stakeholders, data consumers, and source-system owners to understand analytical and AI use cases and translate graph-based data into consumable relational datasets.
- Design and implement graph-to-relational data models that enable graph-derived insights to be leveraged within Databricks, reporting platforms, and enterprise analytics solutions.
- Develop and maintain scalable ETL/ELT pipelines that extract, transform, and integrate graph data into the enterprise data lake and Lakehouse ecosystem.
- Collaborate with source-system teams to onboard new graph datasets and establish reliable data integration patterns.
- Design and implement graph data models, ontologies, and semantic structures where required to represent complex relationships across enterprise domains.
- Optimize graph extraction, transformation, and loading processes for performance, scalability, and data quality.
- Collaborate with Data Engineers, Data Architects, Data Scientists, and AI teams to make graph data broadly accessible across the enterprise.
- Apply graph analytics and graph-based techniques to uncover relationships, dependencies, lineage, and business insights.
- Provide guidance and best practices on graph technologies, graph data modeling, and graph-to-relational integration patterns.
Skills used in this role
What the employer is looking for
- Proven experience designing and implementing enterprise graph data models and graph-based data solutions.
- Strong understanding of graph technologies and modeling approaches, including Property Graphs (LPG), RDF, ontologies, and semantic modeling.
- Experience with graph databases such as Neo4j, Amazon Neptune, Dydra, or equivalent technologies.
- Hands-on experience with graph query languages such as Cypher, SPARQL, Gremlin, or similar.
- Strong software engineering skills in Python.
- Extensive experience building ETL/ELT pipelines and data integration solutions using technologies such as Apache Spark, Databricks, Airflow, or similar platforms.
- Experience transforming and integrating graph data into relational, analytical, and Lakehouse data models.
- Strong understanding of data modeling techniques for analytics, reporting, and AI workloads.
- Experience working with large-scale enterprise datasets and distributed data platforms.
- Ability to collaborate with business stakeholders, data consumers, and source-system owners to translate requirements into scalable data solutions.
- Experience with DevOps, CI/CD, Infrastructure-as-Code, and production-grade cloud data solutions.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field, with 10+ years of relevant experience.
- Strong analytical, problem-solving, and data modeling capabilities.
- Ability to translate business needs into scalable graph and data integration solutions.
- Excellent communication, consulting, and stakeholder management skills.
- Team player with a proactive, hands-on, and ownership-driven mindset.
- Curious, adaptable, and eager to learn new technologies and approaches.
- Fluent in English, both written and spoken.
- Experience working in Agile teams with a DevOps mindset.
Preferred qualifications
- Experience with Databricks, Delta Lake, Unity Catalog, and Lakehouse architectures.
- Experience with AWS services such as S3, Neptune, Glue, Athena, IAM, and Lambda.
- Experience applying graph technologies to AI, RAG, semantic search, knowledge discovery, or recommendation use cases.
- Experience with graph analytics, Graph Data Science, or graph-based machine learning.
- Experience with code- and config- based data visualization platforms such as Shiny, Dash, Grafana, Splunk, Databricks or similar
Benefits and support
- Compensation and benefits are detailed in the job posting
About NXP Semiconductors
NXP Semiconductors enables secure connections and infrastructure for a smarter world, advancing solutions that make lives easier, better, and safer. As a global semiconductor leader, the company drives innovation in automotive processing, secure connected edge systems, industrial IoT, and mobile communications infrastructure.
- Industry
- Semiconductors
- Company size
- 32169 employees
- Founded
- 2006
- Location
- Eindhoven, Netherlands
- Funding stage
- Public Company
Funding
Public Company
Leadership
Rafael Sotomayor
President and Chief Executive Officer
Bill Betz
Executive Vice President and Chief Financial Officer
Lars Reger
Executive Vice President and Chief Technology Officer
Chris Jensen
Executive Vice President and Chief People Officer
Jennifer Wuamett
Executive Vice President, General Counsel, and Chief Sustainability Officer
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