Modernization Engineer

Accenture in India; Navi Mumbai; On-site; INR 350,000 - 700,000; Full time

Job summary

Accenture in India seeks a forward-thinking Modernization Engineer with an AI-first mindset to design, develop, and deploy enterprise-grade Data Vault 2.0 models across large programs. You will own enterprise vault architecture, modeling standards, and governance, while guiding cross-domain decisions and setting benchmarks for performance and scalability.

The role combines architecture-and-governance with hands-on table design, leading a team of modelers and interfacing with client stakeholders

Qualifications

• 14+ years of experience in Data Modeling Techniques and Methodologies
• 6+ years architecting Data Vault 2.0 models at enterprise scale
• 15 year full-time education required

Responsibilities

• Define and own the enterprise Data Vault 2.0 modeling standards, naming conventions, and governance framework across the program
• Architect the Raw Vault / Business Vault / Information Mart layering strategy for the full platform, not a single domain
• Make and defend cross-domain design tradeoffs (e.g., same-as links vs. hierarchical links, satellite splitting strategy)
• Own capacity/performance architecture decisions — clustering keys, micro-partitioning strategy (Snowflake-specific)
• Lead technical reviews and sign off on modeling decisions made by senior modelers
• Interface with client architects, data governance leads, and executives on modeling strategy
• Mentor and direct a team of 3–8 senior/mid-level modelers
• Own the data model roadmap in alignment with migration/modernization milestones
• Drive automation strategy for DV pattern generation to reduce manual build effort at scale

Skills

Data Modeling Techniques

DV2.0 Architecture

Snowflake internals

Stakeholder Management

Automation tools for DV generation

Education

15 years full-time education

Tools

Where Scape

Vault Speed

biG ENIUS

Job description

Project Role

Modernization Engineer

Project Role Description

Build and test agile and cost effective hosting solutions. Implement scalable, high performance hosting solutions that meet the need of todays corporate and digital applications using both private and public cloud technologies. Develop and deliver legacy infrastructure transformation and migration to drive next-generation business outcomes.

Must have skills

Data Modeling Techniques and Methodologies

Good to have skills

NA

Minimum 15 Year(s) Of Experience Is Required

Educational Qualification

15 years full time education

Summary

Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using Generative and Agentic AI frameworks that drive innovation, efficiency, and business transformation. The person should be able to own the enterprise Data Vault architecture across multiple domains or an entire program. Should be able to set modeling standards, arbitrate cross-domain design conflicts, and is the technical authority client stakeholders and delivery teams elevate to. This would be a mix of architecture-and-governance role along with hands-on table design.

Roles & Responsibilities

• Define and own the enterprise Data Vault 2.0 modeling standards, naming conventions, and governance framework across the program
• Architect the Raw Vault / Business Vault / Information Mart layering strategy for the full platform, not a single domain
• Make and defend cross-domain design tradeoffs (e.g., same-as links vs. hierarchical links, satellite splitting strategy, driving keys for multi-active satellites)
• Own capacity/performance architecture decisions — clustering keys, micro-partitioning strategy (Snowflake-specific), load parallelization
• Lead technical reviews and sign off on modeling decisions made by senior modelers
• Interface directly with client architects, data governance leads, and executive stakeholders on modeling strategy
• Mentor and technically direct a team of 3–8 senior/mid-level modelers
• Own the data model roadmap in alignment with migration/modernization program milestones (e.g., legacy-to-cloud lineage, COBOL/mainframe source integration)
• Drive automation strategy for DV pattern generation to reduce manual build effort at scale

Professional & Technical Skills

• Strong grasp of Generative and Agentic AI, prompt engineering, and AI evaluation frameworks. Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization.
• Must To Have Skills: Proven track record owning DV architecture for at least one large, multi-year program (not just project delivery)
• Deep expertise in Snowflake (or equivalent) internals relevant to DV performance — this needs to be genuine architecture depth, not tool familiarity
• Strong stakeholder management experience — this role is client-facing by design
• Experience integrating legacy/mainframe sources (COBOL, JCL, copybooks) into modern DV models is a strong differentiator, not just a nice-to-have, if this is for a banking modernization context
• Experience with regulatory/compliance-heavy domains (banking, insurance) strongly preferred
• Exposure to automation tools for DV generation (Where Scape, Vault Speed, biG ENIUS) is a plus.

Additional Information

• The candidate must have minimum 14 years of experience in Data Modeling Techniques and Methodologies, with 6+ years specifically architecting (not just building) Data Vault 2.0 models at enterprise scale
• A 15 year full-time education is required.