Modernization Engineer

Overview

Modernization Engineer role focused on owning enterprise Data Vault 2.0 architecture and modeling standards across a multi-year program, acting as the technical authority for client stakeholders and delivery teams.

What you'll do

• 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, including clustering keys, micro-partitioning strategy (Snowflake-specific), and 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

What you'll need

• Minimum 15 years of experience required
• Must have skill: Data Modeling Techniques and Methodologies
• 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
• Strong grasp of Generative and Agentic AI, prompt engineering, and AI evaluation frameworks, with ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization
• 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, with genuine architecture depth rather than tool familiarity
• Strong stakeholder management experience
• 15 years full-time education required

Nice to have

• Experience integrating legacy/mainframe sources (COBOL, JCL, copybooks) into modern DV models, a strong differentiator in a banking modernization context
• Experience with regulatory/compliance-heavy domains (banking, insurance) strongly preferred
• Exposure to automation tools for DV generation (WhereScape, VaultSpeed, biG EON) is a plus

Details

• Location: Mumbai