Overview
Design and maintain enterprise data models that enable scalable analytics, governed data products, AI/ML initiatives, and self-service reporting across Carrier's data platforms. Serve as a bridge between business stakeholders, data engineering teams, governance teams, and analytics consumers to ensure consistent, reusable, and business-aligned data structures.
What you'll do
- 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.
What you'll need
- 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).
- Strong expertise in Enterprise Data Modeling.
- Strong expertise in Data Vault Modeling.
- Strong expertise in Semantic Layer Design.
- Strong expertise in 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.
Nice to have
- 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.
Details
- Full-time role.
- Location: Bangalore.
- Target experience level: 8-12 years.
- Role level: Senior Data Modeler / Lead Data Modeler.
Read the full description and apply on the company’s own careers page.