P2B - Data Analyst Principal

Location: Pune, Maharashtra, India

Job Summary:

The IT Systems Engineer Senior is responsible for providing technical leadership in data analysis, data quality, and SAP data migration initiatives supporting enterprise-wide digital transformation programs. This role combines deep expertise in SAP S/4HANA data migration, governance, and quality with strong analytical capabilities to deliver accurate, reliable, and business-ready data across complex technology landscapes.

The successful candidate will lead end-to-end data migration activities, establish data quality standards, develop scalable migration processes, and partner with business and technical teams to ensure successful delivery of large-scale SAP transformation programs. This individual will also provide thought leadership in data analytics, governance, automation, and continuous improvement while influencing enterprise data management practices.

 

Key Responsibilities:

• Lead end-to-end SAP data migration activities across large-scale SAP S/4HANA transformation programs.
• Analyze legacy data sources and SAP data models to define and execute source-to-target mappings for master and transactional data.
• Perform data profiling, quality assessments, root cause analysis, and data validation to ensure completeness, consistency, and accuracy.
• Drive data cleansing, enrichment, standardization, remediation, and reconciliation activities across multiple business functions.
• Design, build, validate, and execute migration datasets using SAP migration tools including SAP BODS, BDC, and other approved migration technologies.
• Develop reusable migration frameworks, automation capabilities, data quality controls, governance standards, and best practices to support scalable delivery.
• Apply advanced analytical techniques to identify data quality, integrity, redundancy, and integration issues, recommending sustainable solutions across the data lifecycle.
• Create dashboards, reports, metrics, and visualizations that provide actionable insights into data quality, migration readiness, risks, and program health.
• Establish and monitor enterprise data quality metrics and support ongoing data governance initiatives and compliance requirements.
• Support ETL development, transformation, load execution, mock conversions, dress rehearsals, cutover planning, production deployment, and post-go-live stabilization.
• Collaborate closely with business stakeholders, SAP functional consultants, solution architects, technical teams, and program leadership to ensure successful migration outcomes.
• Provide technical leadership, coaching, and mentoring to data analysts and project teams while promoting best practices in data management and governance.
• Stay current with emerging technologies including AI-assisted migration capabilities, SAP Business AI, SAP Joule, cloud data platforms, and modern data engineering practices.

About Us

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.The IT Systems Engineer Senior is responsible for providing technical leadership in data analysis, data quality, and SAP data migration initiatives supporting enterprise-wide digital transformation programs. This role combines deep expertise in SAP S/4HANA data migration, governance, and quality with strong analytical capabilities to deliver accurate, reliable, and business-ready data across complex technology landscapes. The successful candidate will lead end-to-end data migration activities, establish data quality standards, develop scalable migration processes, and partner with business and technical teams to ensure successful delivery of large-scale SAP transformation programs. This individual will also provide thought leadership in data analytics, governance, automation, and continuous improvement while influencing enterprise data management practices.