Data Platform Engineer (Distributed Systems&Graph Analytics), Mumbai

We're looking for a Data Platform Engineer to take end-to-end ownership of large-scale data pipelines and distributed systems powering a next-generation Graph Analytics platform. What You'll Own Data Pipeline&Platform Engineering Design and build end-to-end data pipelines (batch + streaming) Own large-scale Apache Spark workloads and distributed data processing Implement data ingestion→ transformation → serving layers Manage schema evolution, data contracts, and pipeline reliability Distributed Systems&Scale Work on systems handling high-volume graph datasets (entities + relationships) Optimize for latency, throughput, and fault tolerance Design scalable architectures using Kafka / Spark / Flink / Beam Cloud&Infrastructure Deploy and operate systems on GCP / AWS (GKE, Dataproc, Cloud Run, etc.) Build and maintain CI/CD pipelines for data and microservices Use Docker, Kubernetes, Terraform for infrastructure automation Data Reliability&Observability Implement data quality checks, monitoring, and alerting Ensure data integrity across pipelines and services Build systems to detect drift, inconsistencies, and failures in production APIs&System Integration Work with GraphQL / REST / gRPC APIs for data access layers Ensure seamless integration between data systems and application layers What We're Looking For You have atleast 4 years in Data Engineering / Platform Engineering / Distributed Systems Strong hands-on experience with: Apache Spark / Distributed data processing, Cloud platforms (GCP or AWS), Streaming systems (Kafka / Flink / Beam)Solid programming skills in Python / Java / Scala / Node.js Experience building and owning production data pipelines end-to-end Understanding of: Microservices architecture, Data modeling&large-scale system design Ability to debug and optimize systems in real production environments Why This Role is Different You own systems, not just components You work on real scale (millions→ billions of data points) You solve distributed systems + graph + real-time problems You operate close to production impact, not isolated dev workYou influence architecture from day one in an early-stage environment What You'll Get High ownership, low bureaucracy environment Work on cutting-edge graph + AI-driven data systems Exposure to complex, real-world data problems (fraud, risk, intelligence) Fast growth with direct impact on core platform architecture