Data Engineer Principal

DESCRIPTION

GPP Database Link (https://cummins365.sharepoint.com/sites/CS38534/)

Job Summary:

The Principal Data Engineer is responsible for the architecture, design, and development of Cummins' data analytics platform. This role ensures efficient data processing, storage, and accessibility for analysts and other consumers. The individual collaborates with key business stakeholders, IT experts, and subject-matter specialists to design and deliver optimal data solutions. Additionally, the Principal Data Engineer manages a team of data engineers, driving data strategy, governance, and operational excellence. Though the role category is listed as Remote, this specific position is designated as Hybrid.

• Business & Product Alignment - Collaborate with the Product Owner and stakeholders to understand the product vision and ensure data architecture supports business objectives.
• Data Architecture Strategy & Design - Define and execute the data architecture strategy, overseeing critical programs like Quantum, Unified Data Model, BI Simplification, Product Lifecycle Management, and Customer + Product data quality and governance.
• Enterprise & Federated Architecture Alignment - Partner with CMI Enterprise Data Architecture and AAI Solutions Architecture to align DBU data design and modeling standards while representing DBU projects in CMI Architecture forums.
• Data Modeling & Optimization - Independently design, develop, and maintain Conceptual, Logical, and Physical Data Models to enhance DBU Data & Analytics projects and ensure scalability, efficiency, and performance.
• Pipeline & Infrastructure Development - Create and optimize data pipeline architectures for efficient data ingestion, transformation, and management, ensuring compliance with governance and security standards.
• Process Automation & Scalability - Identify, design, and implement internal process improvements, including automation, infrastructure optimization, and scalable data solutions.
• Governance & Documentation - Establish and document governance processes, maintaining comprehensive data architecture documentation and ensuring adherence to enterprise standards.
• Tool Evaluation & Innovation - Conduct proof-of-concept (POC) evaluations, recommend new data tools, and guide technology adoption to enhance analytics capabilities.
• Technical Leadership & Support - Own developed data models, providing ongoing support for enhancements, performance optimization, and issue resolution to maintain data accuracy and usability.
• Collaboration & Decision Support - Work with executives, product teams, and data professionals to support data infrastructure needs, enabling data-driven decision-making through integrated enterprise-wide data.
• Coaching & Team Development - Mentor and develop less-experienced team members, fostering a high-performance data architecture culture.
• Strategic Partnerships - Build and maintain strong relationships with business partners to drive value creation through data-driven insights and strategies.

• Collaborates - Builds partnerships and works collaboratively with others to meet shared objectives.
• Communicates effectively - Develops and delivers multi-mode communications tailored to different audiences.
• Customer focus - Establishes strong relationships with stakeholders and delivers customer-centric solutions.
• Decision quality - Makes timely and sound decisions that drive organizational success.
• Manages ambiguity - Effectively navigates uncertainty and adapts to evolving business needs.
• Manages complexity - Analyzes intricate problems and develops structured solutions.
• Tech savvy - Anticipates and adopts new digital technologies and methodologies.
• Solution Design - Creates and defines solution architectures that meet business and technical requirements.
• System Solution Architecture - Develops system-wide solutions in alignment with Cummins Technical Reference Model (CTRM) and CLEAN standards.
• Data Quality - Ensures high data integrity and governance across business processes.
• Problem Solving - Applies systematic analysis to resolve issues and implements preventative solutions.
• Values differences - Recognizes and leverages diverse perspectives and cultures within the organization.

• Significant experience in data engineering, architecture, and development, preferably in a leadership capacity.
• Expertise in processing and managing large datasets.
• Proven architecture and design experience in Big Data technologies, including:
• Java, Map-Reduce, SPARK, HBase, Hive, Kafka, SQL, and ODBC.
• Strong background in cloud-based compute clusters and distributed data processing.
• Experience with data extraction tools and handling large file movements in cloud-based environments.
• Extensive experience in database management, including RDBMS and NoSQL databases.
• Experience building analytical solutions and working with IoT technologies.
• Proven track record in Agile software development and DevOps practices.

• SQL & Database Technologies - Strong proficiency in SQL with expertise in Dimensional Modeling and relational database management systems (RDBMS).
• Data Platforms - Hands-on experience with at least one data platform such as Snowflake or Databricks Delta Lake.
• Big Data Solutions - Deep understanding of Big Data processing, storage solutions, and NoSQL systems.
• Data Architecture & Certifications - Professional certifications in Data Architecture are preferred.
• SAP & Integrations - Experience working with SAP data structures and integrations is a plus.

• Bachelor's or Master's degree in a relevant technical discipline (Computer Science, Data Engineering, Information Technology, etc.).
• Equivalent relevant work experience may be considered in lieu of formal education.
• This position may require licensing for compliance with export controls or sanctions regulations.