As an SDE-4 /Lead in the Data Platform team, you’ll play a critical role in building large-scale backend services and distributed data systems that power Navi’s business operations and intelligence. You’ll work 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 components and services that are observable, resilient, and scale efficiently under real-world workloads.

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 – enforce principles of 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, raising the quality bar, and fostering a strong engineering culture
• Make deep technical trade-offs explicit – connect system internals, architectural decisions, and platform costs with clarity
• 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 to align long-term technical strategy with company goals
• Drive innovation by identifying gaps, proposing bold solutions, and creating reusable building blocks that accelerate multiple teams
• Demonstrate thought leadership by anticipating scale challenges, ensuring security/compliance, and contributing to future-readiness of the platform
• Typically requires 8+ years of strong software engineering experience, including proven architectural leadership in large-scale systems

Must Haves

• Deep expertise in modern data lakehouse and distributed data architectures, with hands-on proficiency in Spark, Flink, Kafka, Trino, Presto, Iceberg/Delta Lake, and large-scale storage/compute separation
• Proven track record of building and scaling multi-tenant data platforms, with awareness of cost efficiency, security, compliance, and operational excellence
• Architectural intuition at scale – capable of evaluating trade-offs between performance, latency, fault-tolerance, extensibility, and cost, and making decisions that stand the test of time
• Strong system internals knowledge (compilers, query engines, storage formats, distributed consensus, networking, JVM internals, or equivalent) and ability to explain them with clarity
• Hands-on leadership – ability to mentor senior engineers, drive adoption of engineering best practices, and raise the bar for architectural and operational excellence

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