Data Modeler - Senior

The Senior Data Modeler interprets complex data and transforms it into actionable information that drives business decisions and improves enterprise data usage. This role gathers and analyzes data from multiple sources, identifies patterns and trends, and presents insights to senior leadership. The position champions improvements in overall data quality, data processes, and governance by leveraging advanced analytics, data modeling, machine learning, and modern cloud data platforms.

Key Responsibilities

• Conduct descriptive and diagnostic analytics on diverse data sources and review insights with senior leadership; recommend and implement corrective actions.
• Design, develop, and optimize scalable data models and architectures, including dimensional models, 3NF, and schema designs.
• Apply machine learning techniques on data and metadata to improve data quality and recommend solutions for identified issues.
• Identify patterns, trends, and anomalies in datasets; apply statistical process controls to ensure data reliability.
• Create complex reports and dashboards using advanced business intelligence tools and technologies.
• Develop data profiles for data lake tables and elements; assess data quality, coherence, and integrability across systems.
• Create, evaluate, and maintain data catalog entries; ensure metadata quality and guide product and development teams using catalog insights.
• Analyze complex datasets from multiple sources to reduce redundancy and resolve data lifecycle issues.
• Collaborate on defining and implementing data cleansing rules, standards, and governance solutions.
• Assist in creating and maintaining documentation for key decisions, rules, controls, processes, and training materials.
• Define and integrate new tools, methods, and technologies into data analysis and modeling processes.
• Coach, mentor, and review the work of less experienced team members, providing technical guidance and problem resolution support.

Core Technical Skills

• Data Modeling: Strong expertise in dimensional modeling, 3NF, and enterprise schema design.
• ETL/ELT & Data Engineering: Hands-on experience with modern data engineering tools and pipeline development.
• Big Data & Cloud Platforms: Exposure to open-source Big Data technologies and cloud-based clustered compute implementations.
• Data Profiling & Cataloging: Proficiency with data profiling tools, metadata management, and data catalog platforms (e.g., Azure Purview, Alation).
• Business Intelligence: Advanced experience with BI tools for reporting, dashboards, and data visualization.
• Platforms: Experience working with Snowflake, Databricks, and other modern cloud data platforms.
• AI/ML: Understanding of AI/ML concepts and frameworks, particularly their application in data quality and process optimization.
• Programming: Strong SQL coding skills with exposure to open-source Big Data technologies; experience with SQL and NoSQL querying.

Preferred / Nice-to-Have Skills

• Experience with graph data modeling and graph databases (e.g., Neo4j, TigerGraph).
• Familiarity with Palantir Ontology.
• Exposure to IoT data and related technologies.

Cummins is an equal opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, or other status protected by law.