The Impact You’ll Drive
At Vegapay, data is not a support function - it is a core product enabler. As a
Data Engineer
, you will build the backbone that powers our credit infrastructure, enabling reliable, real-time, and scalable data systems.
Your work will directly influence decision-making across product, risk, and business teams. From designing high-performance pipelines to enabling analytics and ML use cases, you will ensure our data ecosystem is robust, efficient, and built for scale. Simply put, you will turn data into a competitive advantage.
The Hats You Will Wear
Build and scale reliable data pipelines across batch and real-time systems
Design and maintain data lakes and warehouses on AWS/GCP for high performance and availability
Develop scalable ETL/ELT workflows across diverse data sources and formats
Optimize data architecture for performance, cost, and reliability
Implement real-time data processing within a microservices ecosystem
Create reusable data assets and tools for analytics and data science teams
Design efficient data models aligned with product and business needs
Drive automation and continuously improve data workflows and infrastructure
Partner with Product, Business, and Data teams to solve high-impact problems
Establish and enforce best practices across data engineering, including CI/CD, testing, and monitoring
Define and maintain data taxonomy, metadata, and documentation standards
Evaluate and adopt new technologies to strengthen our data stack
The Perfect Fit
3+ years of hands-on experience in data engineering
Strong experience building and scaling data pipelines and architectures
Proficiency in big data technologies (Spark/Flink, Kafka/Kinesis, Hive, etc.)
Strong SQL skills and experience with both relational and NoSQL databases (e.g., Elasticsearch, Cassandra, MongoDB)
Experience with workflow orchestration tools (Airflow, Luigi, etc.)
Solid exposure to AWS or GCP ecosystems
Experience with real-time/stream processing systems
Proficiency in programming languages like Java or Scala
Strong understanding of data modeling, metadata, and data governance principles
Experience working with large-scale structured and unstructured datasets
Familiarity with scalable data stores and distributed systems
Strong problem-solving skills and ability to work in a fast-paced, cross-functional environment
Good understanding of engineering best practices (Agile, CI/CD, testing frameworks)
The Problem We’re Solving
Financial institutions today are held back by legacy systems that are slow, rigid, and expensive to scale. Launching or evolving credit, lending, and UPI products often takes months, requires heavy engineering effort, and limits the ability to create personalized customer experiences.
At the same time, customer expectations have changed - speed, flexibility, and tailored financial products are no longer optional. Banks and fintechs need infrastructure that allows them to innovate quickly, adapt continuously, and scale without friction.
This is where we come in.
At Vegapay, we are building modern, configurable fintech infrastructure that enables banks, NBFCs, and enterprises to design, launch, and manage credit and payment programs with ease. Our platform brings together flexibility, speed, and control - helping our partners unlock new growth opportunities and deliver personalized banking experiences at scale.
The Opportunity Ahead
High ownership: You build it, you own it
Build at the Core of Fintech Infrastructure
Strong engineering culture: Clean code, solid architecture, fast execution
Zero fluff: Minimal bureaucracy, maximum impact
