Lead Data Engineer/Modeler

Role: Lead Data Engineer/Modeler

Location: Bangalore

Full/ Part-time: Full time 

About Carrier 

Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating innovations that bring comfort, safety and sustainability to life. Through cutting-edge advancements in climate solutions such as temperature control, air quality and transportation, we improve lives, empower critical industries and ensure safe transport of food, life-saving medicines and more. Since inventing modern air conditioning in 1902, we lead with purpose: enhancing the lives we live and the world we share. We continue to lead because of our world-class, inclusive workforce that puts the customer at the centre of everything we do. For more information, visit corporate.carrier.com or follow Carrier on social media at @Carrier. 

About the role:

The Senior Data Modeler is responsible for designing and maintaining enterprise data models that enable scalable analytics, governed data products, AI/ML initiatives, and self-service reporting across Carrier's data platforms. The role serves as a bridge between business stakeholders, data engineering teams, governance teams, and analytics consumers to ensure consistent, reusable, and business-aligned data structures that support enterprise reporting, operational insights, and AI-powered solutions.

• Design conceptual, logical, and physical data models for enterprise data products and analytics platforms.
• Develop dimensional, canonical, and semantic data models to support reporting, AI, and business intelligence use cases.
• Create scalable and reusable data structures for Snowflake, Big Query, and cloud-based Lakehouse environments.
• Establish and maintain enterprise data modeling standards, naming conventions, and design best practices.
• Partner with data engineering and architecture teams to optimize data structures for performance, scalability, and maintainability.

• Collaborate with business stakeholders to understand business processes, KPIs, and reporting requirements.
• Translate business requirements into governed and reusable enterprise data models.
• Support the design and evolution of enterprise data products and semantic layers.
• Drive consistency of business metrics and definitions across domains and reporting platforms.
• Participate in solution design sessions and data architecture reviews to ensure alignment with business objectives.

• Partner with Data Governance teams to define master data, reference data, business glossaries, and metadata standards.
• Incorporate data quality, lineage, and governance requirements into model design.
• Support enterprise metadata management and catalog initiatives.
• Design AI-ready data structures that support machine learning, generative AI, RAG, and agentic AI use cases.
• Contribute to enterprise standards for data discoverability, reuse, and compliance.

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or related field.
• 8+ years of experience in Data Modeling, Data Architecture, or Enterprise Data Management.
• Strong expertise in: Dimensional Modeling (Kimball) Enterprise Data Modeling, Data Vault Modeling Semantic Layer Design, Master and Reference Data Management
• Advanced SQL skills and strong understanding of relational and analytical database concepts.
• Hands-on experience with modern cloud data platforms such as: Snowflake, Google Big Query, Cloud Data Warehouses and Lakehouse architectures
• Experience supporting enterprise analytics, reporting, and data product initiatives.
• Strong understanding of data governance, metadata management, and data quality principles.
• Excellent communication skills with the ability to work across business and technical teams.

• Experience with Atlan, Collibra, or similar governance platforms.
• Experience with Looker, Power BI, Qlik, Tableau, or enterprise semantic modeling tools.
• Exposure to AI/ML, GenAI, and enterprise data platforms.
• Experience in Manufacturing, Supply Chain, Finance, ERP, or Product Engineering domains.
• Familiarity with SAP, Oracle, Salesforce, PLM, or other enterprise systems.