Data Transformation and Management Specialist

PowerToFly; Pune District; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Cummins Inc. is seeking a Data Transformation and Management Specialist to design, develop, and maintain scalable data solutions supporting enterprise data integration and analytics.

You will work across supply chain domains to drive data-driven decisions and continuous improvement. The role focuses on building reliable data pipelines, optimizing ETL/ELT processes, and leveraging Azure cloud services for storage, processing, and analytics.

Qualifications

• Minimum 4 years of experience in Data Engineering, Data Integration, Data Management, or related field.
• Experience building and maintaining enterprise-scale ETL/ELT pipelines.
• Experience with cloud-based data platforms, preferably Microsoft Azure.
• Experience designing, optimizing, and managing relational databases.
• Experience supporting analytics, reporting, and BI solutions.
• Experience working with supply chain / manufacturing data is preferred.
• Experience collaborating with cross-functional teams in Agile environments.
• Exposure to AI/ML data preparation and cloud analytics is a plus.

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 movement of data across systems.
• Develop and maintain database solutions, ensuring performance and availability.
• Clean, validate, transform, and enrich raw data for reporting and analytics.
• Monitor data pipelines, databases, and cloud infrastructure to resolve issues and bottlenecks.
• Utilize Azure services to manage data storage, processing, and integration.
• Provide analytical support for supply chain and business functions via data modeling and KPI analysis.
• Analyze supply chain performance metrics to identify trends and improvement opportunities.
• Support inventory optimization, material planning, and planning parameter refinement through data insights.
• Participate in continuous improvement and Six Sigma projects.
• Ensure data governance and compliance across reporting and data solutions.
• Collaborate with data scientists, engineers, and analysts to deliver business solutions.
• Document data architectures, ETL processes, data models, and configurations.
• Develop repeatable analytics and reporting solutions using BI tools.

Skills

Azure

Azure Data Factory

Databricks

Databricks PySpark

Matillion

SQL

Data Pipelines

Data Transformation

Data Quality

BI & Reporting

Supply Chain Analytics

Education

Bachelors in Computer Science/IT/Data Engineering

Tools

Power BI

Python

Scala

Streamlit

Neo4j/Graph DB

Snowflake

Job description

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.

Experience

• 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.

Key Skills

Technical Skills

• 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

Good to Have

• Power BI
• Python
• Scala
• Streamlit
• AI/ML concepts using Databricks or Snowflake
• Neo4j / Graph Database
• Advanced analytics and visualization tools

Core Competencies

• 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.

Qualifications

• College, university, or equivalent Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, Engineering, or a related discipline required.

Job Supply Chain Planning

Organization Cummins Inc.

Role Category On-site with Flexibility

Job Type Exempt - Experienced

ReqID 2434497

Relocation Package No

100% On-Site No