The Role
Designs and maintains scalable data pipelines, ETL processes, databases, and cloud-based data platforms. Ensures data quality, governance, integrity, and availability while supporting business intelligence, reporting, and supply chain analytics. Analyzes KPIs, inventory, and material planning data to identify improvement opportunities. Collaborates with technical and business stakeholders, troubleshoots performance issues, documents data solutions, and supports continuous improvement initiatives using Azure, Databricks, SQL, and related technologies.
Summary Generated by Built In
The Data Transformation and Management Specialist is responsible for designing, developing, and maintaining scalable data solutions that enable efficient data integration, transformation, and analytics across the organization. This role combines data engineering expertise with supply chain analytics to support business decision-making, improve operational performance, and drive continuous improvement initiatives. The specialist ensures the integrity, availability, and quality of enterprise data while collaborating with cross-functional teams to deliver reliable data pipelines, reporting solutions, and cloud-based data platforms.
Key Responsibilities- Design, develop, and maintain scalable data pipelines to acquire, transform, and load data from multiple enterprise systems using batch and real-time processing methods.
- Build, optimize, and maintain ETL processes to ensure reliable, automated, and efficient movement of data across systems.
- Develop and maintain database solutions, ensuring optimal performance, scalability, and data availability.
- Clean, validate, transform, and enrich raw data to improve quality, consistency, and usability for reporting and analytics.
- Monitor data pipelines, databases, and cloud infrastructure to identify and resolve performance issues, data quality concerns, and system bottlenecks.
- Utilize cloud technologies, particularly Microsoft Azure services, to manage data storage, processing, and integration.
- Provide analytical support for supply chain and business functions through data modeling, reporting, and KPI analysis.
- Analyze supply chain performance metrics to identify trends, root causes, improvement opportunities, and actionable recommendations.
- Support inventory optimization, material planning, and planning parameter refinement through data-driven insights.
- Participate in continuous improvement initiatives, including Six Sigma and supply chain optimization projects.
- Ensure data integrity, governance, and compliance across reporting, analytics, and enterprise data solutions.
- Collaborate with data scientists, software engineers, business analysts, and functional stakeholders to understand data requirements and deliver business solutions.
- Develop and maintain documentation for data architecture, ETL processes, data models, and system configurations.
- Support the development of repeatable analytics and reporting solutions using enterprise business systems and Business Intelligence tools.
- Minimum 4 years of experience in Data Engineering, Data Integration, Data Management, or a related field.
- Experience developing and maintaining enterprise-scale ETL/ELT pipelines.
- Experience working with cloud-based data platforms, preferably Microsoft Azure.
- Experience designing, optimizing, and managing relational databases.
- Experience supporting analytics, reporting, and business intelligence solutions.
- Experience working with supply chain, manufacturing, or enterprise business data is preferred.
- Experience collaborating with cross-functional teams in Agile or project-based environments.
- Experience with data quality, monitoring, troubleshooting, and performance optimization.
- Exposure to AI/ML data preparation and cloud analytics platforms is an advantage.
- Microsoft Azure (Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure SQL Database)
- ETL/ELT development using Databricks PySpark and Matillion
- Relational Databases: Oracle, SQL Server, PostgreSQL, Snowflake
- Data Engineering and Data Pipeline Development
- Database Design and Performance Optimization
- Data Transformation, Data Cleansing, and Data Quality Management
- SQL and Advanced Query Optimization
- Cloud Data Architecture and Data Integration
- Business Intelligence and Reporting
- Supply Chain Analytics and KPI Reporting
- Inventory Optimization and Material Planning Analytics
- Documentation and Technical Process Management
- Power BI
- Python
- Scala
- Streamlit
- AI/ML concepts using Databricks or Snowflake
- Neo4j / Graph Database
- Advanced analytics and visualization tools
- Communicates effectively with technical and business stakeholders.
- Drives results while managing competing priorities and deadlines.
- Demonstrates a global perspective and supports enterprise-wide solutions.
- Solves complex business and technical problems using analytical thinking.
- Optimizes work processes through automation and continuous improvement.
- Applies strong analytical and troubleshooting skills to data and supply chain challenges.
- Supports inventory management, material planning, and supply chain optimization through data-driven decision making.
- Manages and interprets KPIs to identify business improvement opportunities.
- Values diverse perspectives and collaborates effectively across global teams.
- Maintains a strong focus on data accuracy, governance, and operational excellence.
- College, university, or equivalent Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, Engineering, or a related discipline required.
Skills Required
- At least 4 years of experience in data engineering, data integration, data management, or a related field
- Experience developing and maintaining enterprise-scale ETL or ELT pipelines
- Experience working with cloud-based data platforms, preferably Microsoft Azure
- Experience designing, optimizing, and managing relational databases
- Experience supporting analytics, reporting, and business intelligence solutions
- Experience collaborating with cross-functional teams in Agile or project-based environments
- Experience with data quality, monitoring, troubleshooting, and performance optimization
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, Engineering, or a related discipline
- Experience with supply chain, manufacturing, or enterprise business data
- Exposure to AI/ML data preparation and cloud analytics platforms
Cummins Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cummins and has not been reviewed or approved by Cummins.
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Retirement Support — A 401(k) with company contribution/match and both defined contribution and defined benefit pension plans are offered, alongside profit sharing and an employee stock purchase plan. This mix supports long-term savings and financial security.
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Healthcare Strength — Multiple medical plan options (HSA, HSA Plus, PPO) with dental, vision, life and long-term disability coverage are provided, along with telehealth, mental-health support, and wellness tools. In-network protections and HSA/HSA Plus structures are described to help manage costs.
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Parental & Family Support — Paid maternity and paternity leave, family medical leave, and adoption assistance are offered. Reduced or flexible hours and unpaid extended leave options further support caregiving needs.
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The Company
What We Do
At Cummins, we empower everyone to grow their careers through meaningful work, building inclusive and equitable teams, coaching, development and opportunities to make a difference. Across our entire organization, you'll find engineers, developers, and technicians who are innovating, designing, testing, and building. You'll also find accountants, marketers, as well as manufacturing, quality and supply chain specialists who are working with technology that's just as innovative and advanced.
