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Technical Lead, IT​/Tech, Data Engineer

Job in Bengaluru, 560001, Bangalore, Karnataka, India
Listing for: Vymo
Full Time position
Listed on 2026-06-07
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager, Data Analyst, Business Systems/ Tech Analyst
Job Description & How to Apply Below
Location: Bengaluru

Technical Lead - Nova

About Vymo

Vymo transforms how financial institutions manage their distribution networks and collections operations. Our AI-powered DMS and CMS platform serves 350,000+ users across 70+ global financial enterprises, enabling banks and insurers to optimize performance across their distribution channels, and empowering banks to drive operational excellence in collections.

Why Global Leaders Choose Vymo

Vymo partners with financial institutions through a comprehensive solution that combines deep domain expertise with cutting-edge technology. Our platform's human-centric design, coupled with enterprise-grade scalability and AI-powered intelligence, delivers measurable business outcomes while ensuring high user adoption and engagement.

Recognition & Trust

● Backed by $45M+ funding from Peak XV partners (formerly Sequoia), Emergence Capital, and Bertelsmann Investments.

● Trusted by leading global financial institutions including Berkshire Hathaway, AIA, AXA, SBI Life, HDFC Bank, Aditya Birla Capital, Tata AIA, ABSLI and many more!

● Recognized by Celent in their 2024 Distribution Management Solutions report, with an Advanced Functionality ranking.

● Featured in Gartner's Market Guide for Sales Engagement Applications and recognize
d as a"Strong Performer" in Forrester's Sales Engagement Wave Report.

● Microsoft 'AI for All' award winner for innovation in artificial intelligence.

Explore Vymo on   

About the Role
We are looking for a Technical Lead to join team  Nova  to drive the architecture and development of both backend systems and data platforms s role sits at the intersection of  application engineering and data engineering , with a strong focus on  metrics, analytics infrastructure, and scalable data systems . You will lead the design of high-performance services as well as data pipelines and analytics layers powering business insights.

About Nova

Team Nova builds the data and platform infrastructure that powers analytics, operational intelligence, and large-scale business workflows across Vymo. We work on high-scale backend and data engineering problems spanning:

Real-time and batch data pipelines, Building resilient ingestion and ETL pipelines
Designing efficient OLAP schemas and large-scale analytical workloads in Click House
Large-scale data transfer and synchronization between Postgre

SQL and Click House
Click House data modeling and query optimization
Improving performance, reliability, and scalability of data systems
Metrics platforms, dashboards, and analytical systems
Java-based microservices, distributed backend systems that power key metrics and data access
High-volume event processing and operational observability

Our team is responsible for designing scalable data architectures that enable fast, reliable, and actionable insights for both internal systems and customer-facing products. We operate at the intersection of backend engineering, data infrastructure, and platform scalability. If you enjoy building scalable platforms, working with large datasets, and designing systems that directly influence product intelligence and business decision-making, Team Nova is the place for you.

Key Responsibilities

Backend & Platform Engineering
Design and implement scalable microservices using  Java (Spring Boot)  /  Node.js .
Build high-performance APIs and distributed systems.
Implement  caching strategies  (Redis/Memcached) to optimize latency and throughput.
Ensure system reliability, scalability, and maintainability in production.

Data Engineering & Analytics Infrastructure
Design and implement  data pipelines (batch & streaming)  based on product and analytics requirements.
Build and optimize  Click House schemas and queries  for large-scale analytics workloads:
Efficient ingestion pipelines
Partitioning and indexing strategies
Query performance tuning
Implement data transformations and aggregation layers for downstream consumption.

Metrics & Data Systems
Implement systems for  metrics computation and aggregation  (real-time or batch).
Ensure correctness, consistency, and efficiency of data processing pipelines.
Optimize storage and retrieval for high-volume event data.

Dashboards & Data Access
Build…
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