Cummins Inc.
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Pune · On-site · 8-11 Yrs · Oct 13
Transportation Equipment Manufacturing · 10000+ Employees · Columbus, US
Cummins is a place big enough to coach and develop a global workforce and create the world’s leading clean, engine technology. We’re also small enough for you to find your fit and personal passion with a team of dependable, innovative thinkers who are developing their careers within a diverse, inclusive, empowering environment. Cummins Inc., a global power technology leader, is a corporation of complementary business units that design, engineer, manufacture, distribute and service engines and related technologies, including fuel systems, controls, air handling, filtration, emission solutions and electrical power generation systems. Headquartered in Columbus, Indiana, we employ 60,000+ people worldwide and serve customers in approximately 190 countries and territories through a network of more than 500 company-owned and independent distributor locations and approximately 7,500 dealer locations. Cummins had net income of $1 billion and revenues of $20.4 billion in 2017.
Hiring: Engineering
What employees say
+ Workload less Supportive management Good stipend
− Not much; it depends on management and the business unit.
More reviews on the company profile.
Interview experience · Software Engineer
It was good. Only 1 round happened and right after that i got an offer letter. Onboarding was smooth. HR was very supportive throughout the process. It was a good experience
Easy difficulty · India · 187 reports
More interview insightsJob description
Overview
Minimum 8 Years experience require:
Responsibilities
- Lead the design, governance, and continuous evolution of enterprise data models and data products, including conceptual, logical, and physical data modelling. Review and approve data model changes, new source integrations, tables, attributes, and relationships introduced across data products to ensure alignment with enterprise data architecture standards, modelling principles, scalability, reusability, and business requirements.
- Design and build reliable, high-performance data engineering solutions including data ingestion, transformation, integration, and orchestration pipelines across cloud data platforms, ensuring data quality, security, governance, scalability, and operational excellence throughout the enterprise data lifecycle across Supply Chain, Quality, Finance, Product Lifecycle, and other Enterprise Products domains.
- Partner with Data Engineers, Solution Engineers, Analysts, and Business Stakeholders to translate business requirements into governed, discoverable, and AI-ready data products by applying Data-as-a-Product principles, metadata standards, lineage, semantic modelling, and data governance practices that enable trusted enterprise data
Qualifications
- Strong experience in enterprise data modelling and data engineering, supporting large-scale data warehouses, lakehouses, semantic models, and enterprise data products on modern cloud platforms.
- Strong expertise in enterprise data modelling, including conceptual, logical, and physical data models, dimensional modelling (Star/Snowflake), Data Vault, normalized and canonical models, semantic modelling, master data management, and enterprise data architecture standards.
- Proven experience governing and reviewing enterprise data models across multiple data products, including evaluation of new source systems, entities, attributes, relationships, and model enhancements to ensure alignment with enterprise architecture principles, data standards, scalability, reusability, and long-term maintainability.
- Experience designing and implementing data solutions across the complete data lifecycle, including Source Systems, Data Ingestion, Raw/Bronze, Curated/Silver, Business/Gold, Semantic Layers, and Enterprise Data Products, ensuring data quality, governance, security, performance, and operational excellence.
- Strong hands-on expertise in data engineering and cloud data platforms, including Snowflake, Databricks, SQL, Matillion, dbt,Power BI with experience building scalable, high-performance data pipelines, data integration solutions, and reusable enterprise data assets.
- Proven ability to lead technical design and data model reviews and collaborate with Solution Engineers, Data Engineers, Architects, and Business Stakeholders to translate business requirements into scalable data products and establish enterprise-wide data modelling, engineering, and governance best practices.
- Experience implementing data quality frameworks for Supply Chain, Quality, Finance, Product Lifecycle, and other Enterprise Products domains.within large-scale Data Modernization or Data-as-a-Product initiatives.
- Experience applying AI/ML and Data Observability capabilities to Data Quality, including anomaly detection, predictive quality monitoring, automated root cause analysis, AI-ready data certification, and governance controls supporting Analytics, Machine Learning, and GenAI solutions.
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Job application FAQ
Last updated 16 October 2026
- How do I apply for Data Engineer-Senior at Cummins Inc.?
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- This listing is marked on_site with location Pune, Maharashtra. Confirm details on the job description before applying.
- What skills matter for this Data Engineer-Senior role at Cummins Inc.?
- This is a senior Data Engineer-Senior role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.