Description

We are seeking a highly experienced MongoDB Architect to lead a large-scale legacy data modernization initiative, involving migration of old mainframe-based data systems into a modern MongoDB ecosystem.

This role requires deep expertise in data discovery, reverse engineering, canonical data modeling, and NoSQL schema design, along with the ability to handle highly complex, undocumented legacy systems.

Lead end-to-end data architecture and migration strategy from legacy mainframe systems to MongoDB
Perform data discovery and reverse engineering of undocumented / poorly documented systems
Analyze mainframe data structures (VSAM, flat files, hierarchical data, etc.)
Define and design canonical data models for enterprise-wide usage
Design optimized MongoDB document models (collections, embedding, referencing)
Establish data transformation, cleansing, and mapping strategies
Build data migration frameworks, pipelines and data Archival strategy
Ensure data consistency, integrity, and reconciliation during migration
Implement MongoDB best practices (indexing, sharding, replication,



performance tuning)
Collaborate with business stakeholders to understand implicit data relationships and rules
Define data governance, metadata, and lineage frameworks
Support validation, testing, and post-migration stabilization
Mentor teams on NoSQL design principles and migration approaches
API design on the top of the MongoDB Atlas
Hands on experience in configuring MongoDB Atlas cluster

Role

MongoDB & NoSQL Expertise

Deep hands-on experience with MongoDB architecture
Migrating from RDBMS/SQL to MongoDB/NoSQL
Knowledge of MongoDB (Replica Sets, Sharding, Aggregation Framework)
Familiarity with GCP cloud platforms
Strong expertise in:
Document data modeling
Schema design (embedding vs referencing)
Indexing, aggregation framework
Sharding and replication
? Data Modeling & Architecture

Expertise in canonical data modeling
Robust experience in:
Data normalization vs denormaliza

📌 Lead MongoDB (Indore)
🏢 Impetus
📍 Indore