enterprise data modeler

As a hiring partner for many IT organizations , we are looking for Enterprise Data Modeler as Sr. Data Engineer. interested candidates can share word format resume with details at info@unimorphtech.com Job Title: Sr. Data Engineer (EDM) - Analytics Experience : 10+ Yrs ( 5+ Yrs Relevant Exp Data Architecture & Data Modelling) Location:Chennai # Purpose :The Data Engineer (EDM) is responsible for designing a highly scalable, agile Enterprise Data Warehouse (EDW) utilizing Data Vault 2.0 methodology. You will solve complex data modelling challenges while championing AI-assisted development tools to automate and accelerate the generation of data models, mappings, and standardized Data Vault boilerplate code. Note : Candidate must be Expert in enterprise data modelling,data architecture,Snowflake,data vault design,DWH. # Key Skills : Data architecture,Data modelling,Logical and Physical data modeling,Data valut 2.0 certified, data vault architecture,Snowflake,Azure,synapse,DBT,AI tools integration i.e. GitHub, Copilot into Data model. # Must Have : Hands on Data Vault 2.0 methodology, AI-coding assistants, data modeling tools (Erwin, Hackolade), Snowflake/Azure, and dbt. # Highlights : Typical Activities: Facilitating modeling workshops to identify core business concepts, designing Point-in-Time (PIT) and Bridge tables, and reviewing automated/AI-generated dbt models or SQL scripts to ensure they meet Data Vault 2.0 standards. Tools/Technologies: Data Vault 2.0 methodology, AI-coding assistants, data modeling tools (Erwin, Hackolade), Snowflake/Azure, and dbt. AI-Driven Efficiency:- Integrate AI-assisted development tools e.g.GitHub Copilot into Data model for automation. Enterprise data architecture strategy,pattern,data retention,data Auditing,GRC,data integration. GRC : Establish Data modeling standards,Data governance,data standards,data lineage,compliance etc. Technical leadership to data modelers and data engineers Capability Building for Data Vault 2.0 ,best practices,secure use of AI-coding tools. expertise in designing and implementing Data Vault 2.0 architectures (Hubs, Links, Satellites, Hash Keys, PIT/Bridge tables). # Responsibilities : Design and own the conceptual, logical, and physical data models, specifically implementing Data Vault 2.0 architecture (Hubs, Links, Satellites). AI-Driven Efficiency: Integrate AI-assisted development tools (e.g., GitHub Copilot) into the data modeling and engineering workflows to automate repetitive SQL/DDL generation and speed up delivery. Strategic Influence: Define the overarching data architecture strategy, establishing patterns for historical data retention, auditability, and integration across the global enterprise. Stakeholder Collaboration: Act as the bridge between business domains and technical teams, translating complex business ontologies into robust Data Vault structures. Governance & Standards: Establish strict data modeling standards, hashing rules, and data lineage tracking while ensuring the architecture supports compliance and data privacy. Provide technical leadership to a global team of data modelers and engineers. Capability Building: Act as the internal educator for both Data Vault 2.0 best practices and the effective, secure use of AI-coding tools to populate Hubs, Links, and Satellites efficiently. # Experience : Bachelors or Masters degree in Computer Science, Information Systems, or a related technical field. 10+ years of overall IT/Data experience, with at least 5+ years dedicated to Enterprise Data Architecture and Data Modeling. Deep, proven expertise in designing and implementing Data Vault 2.0 architectures (Hubs, Links, Satellites, Hash Keys, PIT/Bridge tables). Practical experience implementing and guiding teams on AI-assisted development tools (GenAI, LLMs, Copilot) to accelerate data engineering and modeling workflows. Advanced SQL proficiency and hands-on experience with modern cloud data platforms (e.g., Snowflake, Azure Synapse).