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MongoDB Lead

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Hybrid

MongoDB Lead

Agile Ventures

MongoDB Lead

Skills

Google Cloud PlatformSQL QueriesMongoDBPythonAWSCOBOLAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

17 September 2026

What they need


We are seeking a highly experienced MongoDB Lead 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

Roles

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

  • Strong experience in:

  • Data normalization vs denormalization

  • Designing enterprise-wide data models

  • Mapping legacy data to modern schemas

Data Migration & Engineering

  • Experience in large-scale data migration programs (Migrating from RDBMS/SQL to MongoDB/NoSQL)

  • Knowledge of:

  • ETL/ELT processes

  • Data transformation and cleansing

  • Data reconciliation techniques

  • Experience with tools like Spark / Python / data pipelines

Legacy System Understanding (Good to have)

  • Strong experience with mainframe data systems

  • Knowledge of:

  • VSAM files

  • COBOL copybooks

  • Flat files / hierarchical data structures

  • Ability to work with missing or undocumented codebases

Problem Solving & Analysis

  • Strong analytical skills to interpret legacy data without documentation
  • Ability to infer business rules from data patterns

Performance & Scalability

  • Experience in performance tuning MongoDB workloads
  • Ability to design for high-volume, high-velocity data systems

Preferred Qualifications

  • Experience in banking / insurance / government legacy systems
  • Exposure to data governance frameworks
  • Familiarity with cloud platforms (AWS/GCP/Azure)
  • Experience with data cataloging and metadata tools
  • MongoDB certifications (Developer/DBA)

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