Enterprise Data Architect

Important Company Update - Please Read Before Applying. On January 22, 2025, Aptiv announced its decision to separate its EDS division to form two separate independent companies:https://www.automotiveworld.com/news-releases/aptiv-announces-intention-to-separate-its-electrical-distribution-systems-business/

This role is within the EDS segment, and you will be joining that segment as it becomes its own entity, with a rich heritage and proven track record as a global leader in low and high voltage power and signal distribution systems. Our solutions are central to enabling the next generation of electrified, automated, and connected vehicles, and we are committed to innovation, sustainability, and engineering excellence.

We are looking for talented individuals who are excited by the opportunity to help shape the future of EDS and delivering industry-leading solutions to the world's top automotive manufacturers

Your Role

A Data Architect designs and implements enterprise data management systems that align with business needs and strategic goals. This role bridges technical expertise with business understanding to create scalable, efficient data infrastructure.

Key Responsibilities

• Design and implement comprehensive data architecture frameworks and data models
• Develop data management strategies, governance policies, and quality standards
• Create and maintain data dictionaries, taxonomies, and metadata repositories
• Collaborate with stakeholders to understand business requirements and translate them into technical specifications
• Establish data integration processes between disparate systems
• Implement security measures to protect sensitive data
• Evaluate and recommend appropriate data storage solutions (relational databases, data warehouses, data lakes)
• Guide ETL processes and data pipeline development
• Mentor data engineers and analysts on best practices

• Data Modeling: Expertise in conceptual, logical, and physical data modeling techniques
• Database Technologies: Proficiency with relational databases, NoSQL solutions, data warehouses, and data lakes
• Big Data Frameworks: Knowledge of Hadoop, Spark, Kafka, and other distributed processing systems
• ETL/ELT Processes: Design and optimization of data integration pipelines
• Data Governance: Implementing data quality, master data management, and metadata management
• SQL & Query Optimization: Advanced SQL skills and performance tuning expertise
• Cloud Data Platforms: Experience with AWS, Azure, or GCP data services
• Data Security: Understanding of data protection, encryption, access controls, and compliance requirements

• Data Strategy Development: Aligning data architecture with business objectives
• Enterprise Architecture: Understanding how data architecture fits within broader enterprise systems
• Data Lifecycle Management: Policies for data retention, archiving, and disposal

• Communication: Explaining complex data concepts to non-technical stakeholders
• Collaboration: Working effectively with data engineers, analysts, scientists, and business teams
• Problem-Solving: Addressing complex data challenges with innovative solutions
• Documentation: Creating comprehensive data dictionaries, models, and architectural diagrams
• Project Management: Coordinating data architecture initiatives across teams