Staff Engineer ( Backend )

Acceldata is reimagining the way companies observe their Data! Acceldata is the pioneer and leader in data observability, revolutionizing how enterprises manage and observe data by offering comprehensive insights into various key aspects of data, data pipelines and data infrastructure across various environments. Our platform empowers data teams to manage products effectively by ensuring data quality, preventing failures, and controlling costs. A days in the life of a Staff Backend Engineer Architect, design, and implement highly scalable distributed systems using Java, applying microservices and event-driven design patterns to solve complex engineering problems. Write production-grade, efficient, and maintainable code with a strong focus on data structures, algorithms, concurrency, and system-level optimizations. Lead end-to-end system design, including API contracts, service decomposition and trade-off analysis (latency, throughput, consistency, fault tolerance). Build and optimize low-latency, high-throughput APIs and backend services, ensuring reliability, resiliency, and observability at scale. Deep dive into performance bottlenecks using profiling, benchmarking, and debugging tools. Design and implement distributed data processing pipelines and handle large-scale datasets with a focus on scalability and fault tolerance. Own critical components, drive code reviews, design reviews, and enforce high engineering standards (testing, CI/CD, clean architecture). Collaborate closely with Product, Data, and DevOps teams while also influencing technical roadmap and architectural direction. Mentor engineers through pair programming, code walkthroughs, and design guidance, raising the overall technical bar of the team. You are a great fit for the role, if you have 12–15 years of hands-on experience in backend development using Java. Strong understanding of distributed systems, system design, and microservices. Experience in building data processing pipelines using Apache Spark or Apache Flink. Experience with NoSQL databases (e.g., Cassandra, MongoDB, DynamoDB). Solid experience in building large-scale, cloud-native systems. Working knowledge of Databricks or Snowflake or Big Data technologies is preferred. Excellent problem-solving, debugging, and analytical skills. Strong ownership and ability to work in a fast-paced product environment.