Data Engineer Principal

GPP Database Link

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.

Key Responsibilities:

• Gather requirements and build roadmaps, architectures, and lead tool selection processes to help Product Teams achieve their goals.
• Serve as a trusted partner, collaborating and aligning with the broader Organization and Enterprise Data Strategy.
• Design data architectures for data lakes, databases, and data warehouses based on functional and technical requirements.
• Create and maintain optimal data pipeline architectures for efficient data ingestion, transformation, and management.
• Identify, design, and implement internal process improvements, including automation, data optimization, and infrastructure redesign for scalability.
• Work with executives, product teams, and data professionals to support data infrastructure needs and resolve technical challenges.
• Ensure compliance with data governance and security requirements while enhancing integrated and reusable data pipelines.
• Develop troubleshooting methods and failure mode analysis across the entire data flow, advocating for a strong data quality culture.
• Enable executive decision-making by integrating data from multiple source systems across the organization.
• Work closely with data and analytics experts to improve functionality and performance in data systems.
• Coach and mentor less-experienced team members to foster a high-performing data engineering culture.
• Develop and maintain strong relationships with business partners to drive data-driven value creation.

• 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.

• Strong proficiency in SQL and Dimensional Modeling.
• Expertise in at least one data platform such as Snowflake, Databricks Delta Lake.
• Deep understanding of Big Data processing and storage solutions.
• Strong knowledge of database technologies (SQL and NoSQL systems).
• Professional certifications in Data Architecture are preferred.
• Experience working with SAP data structures and integrations is a plus.

• Bachelors or Masters 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.

Competencies:

• 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.