About the Role

As part of the Data Platform team, you'll build large-scale backend services and distributed data systems powering KreditBee's business operations and intelligence working on high-throughput, low-latency infrastructure that processes billions of events and transactions with high reliability. You'll collaborate closely with senior engineers to deliver well-architected, observable, resilient, and scalable components.

What We Expect From You

- Architect and drive large-scale distributed systems, data platforms, and backend services that are highly available, cost-efficient, secure, and extensible
- Establish platform vision and evolve foundational frameworks with multi-tenant, self-serve, and platform-first thinking
- Design for scale and resilience enforcing clean architecture, observability, fault tolerance, extensibility, and performance
- Lead end-to-end initiatives from problem definition to production rollout, balancing business impact with long-term technical sustainability
- Mentor and grow engineers (including Senior Engineers), setting technical direction and raising the quality bar
- Make deep technical trade-offs explicit — connecting system internals, architectural decisions, and platform costs
- Champion best practices in code quality, instrumentation, design patterns,



and cloud-native development
- Influence cross-team architecture by partnering with product, infra, and data science
- Drive innovation by identifying gaps, proposing bold solutions, and creating reusable building blocks
- Demonstrate thought leadership by anticipating scale challenges and ensuring security/compliance.

Must Haves

- Deep expertise in modern data lake/warehouse and distributed data architectures — hands-on with Trino, Presto, Iceberg/Delta Lake, Spark, Kafka, and large-scale storage/compute separation
- Coding proficiency in Golang or Python
- Proven track record building and scaling multi-tenant data platforms, with awareness of cost efficiency, security, compliance, and operational excellence
- Architectural intuition at scale — evaluating trade-offs between performance, latency, fault-tolerance, extensibility, and cost
- Solid system internals knowledge (compilers, query engines, storage formats, distributed consensus, networking, JVM internals, or equivalent)
- Hands-on leadership — mentoring senior engineers and driving adoption of engineering best practices

Mandate Skills:

- Python
- Snowflake
- Trino
- Iceberg
- Golang

📌 Senior Platform Engineer (Bengaluru)
🏢 Krazy Bee Services
📍 Bengaluru