Technical Lead – Data Platform

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 recognized as a

"Strong Performer" in Forrester's Sales Engagement Wave Report.

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

The Role

Team Nova builds the high-scale data infrastructure, metrics engines, and operational intelligence workflows that power Vymo globally. As a Lead Engineer, you will sit at the absolute intersection of application backend design and massive data platform engineering. You will own the architecture, scalability, and performance of distributed microservices and OLAP databases that process high-volume transactional events and turn them into real-time, actionable business insights.

What You Will Do

Backend & Data Infrastructure Architecture (50%)

• System Design: Architect, scale, and optimize distributed, high-volume Java microservices and event-driven backend systems.
• OLAP Engineering: Own large-scale data modeling, schema design, and query optimization within ClickHouse to power real-time analytics.
• Data Sync & Ingestion: Design and optimize real-time and batch data pipelines (ETL/ELT) for high-fidelity data synchronization between PostgreSQL and ClickHouse.

Technical Leadership & Platform Reliability (50%)

• Drive Engineering Standards: Guide engineering pods on design patterns, write production-grade code, and enforce strict code quality through rigorous reviews.
• Scale Data Platforms: Continuously eliminate performance bottlenecks, improve system reliability, and scale high-volume event processing systems.
• Own the Metrics Layer: Architect the foundational metrics platforms, dashboards, and operational observability pipelines that feed internal and external products.

What You Will Bring

Experience & Fluency

• Engineering Longevity: 710+ years of core software engineering experience, including 2+ years leading technical pods, driving system architecture decisions, and mentoring senior engineers.
• Dual-Stack Programming Mastery: Elite hands-on coding proficiency across asynchronous environments. Deep mastery of Java (Spring Boot, distributed microservices) paired with strong production experience in Node.js (Express/NestJS) and Python/SQL for data workloads.
• OLAP & Storage Expertise: Deep, real-world production experience with distributed analytical column-stores, specifically ClickHouse. Combined with a bulletproof mastery of relational databases (PostgreSQL) and distributed caching layers (Redis).
• Data Streaming Infrastructure: Proven track record of building highly resilient, real-time and batch ingestion pipelines. Expert handling of distributed message brokers and queues (Kafka / RabbitMQ) under heavy event traffic.
• Systems Architecture & BI Delivery: Strong foundational understanding of distributed systems design, data serialisation formats, and analytics visualization tools (Apache Superset or similar BI frameworks).

Mindset and Core Traits

High-Agency Technical Execution

• Extreme Ownership: You do not wait for product requirements to be perfectly spelled out or hand-held by a project manager. You look at business goals, map the system dependencies, and build the technical execution script as you go.
• Defensive Engineering Bias: You build with a "Zero-Trust" mindset regarding upstream data quality. When building pipelines between transactional databases (PostgreSQL) and analytical warehouses (ClickHouse), you design self-healing loops that automatically handle sudden schema changes or dropped connections without dropping stream state or creating data duplication.

The Engineering team at Vymo is looking at Stellar Engineers who will not only build the engineering systems but a culture of engineering excellence. If this is interesting do explore!