Akhilesh Rane

• Developed a Redis-backed API rate limiter using the token bucket algorithm to enforce per-API request quotas. • Architected and implemented backend services in Java and Android for multiscan barcode verification on Zebra handheld devices, processing 50k + scans/day, while introducing health checks to improve operational reliability. • Improved performance of a high-traffic API by 25–50x through query batching, caching, and reduction of database round trips. • Built an event-driven processing pipeline using AWS SQS and S3 for supply chain transaction events, enabling asynchronous response handling, delivery confirmation, and downstream validation workflows. • Worked on migration from Java 8 to Java 11 across 5+ Java+Scala microservices, ensuring compatibility and stability via phased roll-out. • Resolved concurrency issues in serial number updates by implementing user-scoped locking, improving consistency under concurrent access scenarios. • Reduced build times by 30–40% by enabling incremental compilation using Zinc across Java and Scala modules. • Partnered with incident management and support teams to troubleshoot production escalations, perform root cause analysis, and develop internal tooling for production data repair operations. • Mentored engineers and contributed to architectural standards, design reviews, and cross-team technical decisions. • Resolved a command injection vulnerability through input validation, parameterized execution, and command whitelisting to improve application security.

• Designed and implemented a multithreaded job scheduler (Java, Spring Boot, Spark) to orchestrate dependent workflows and improve execution reliability across distributed processing pipelines. • Built a microservices-based ETL and warehousing platform using Java, Scala, Spring Boot, Spark, SQL and Hive to ingest and transform data from MySQL, Oracle, and Netezza systems. -- 1 of 2 -- • Developed scalable Spark-based reporting and analytics tools supporting CSV, XLSX, PDF, and HTML outputs, including advanced Excel generation using Apache POI. • Improved scalability and cluster resource utilization by migrating Spark workloads from client mode to cluster mode, reducing dependency on driver-node execution. Improved code quality and reliability via unit testing using JUnit and Mockito. • Designed automated recovery and reprocessing mechanisms for failed data feeds, improving resiliency and reducing operational intervention for pipeline failures. • Implemented custom Hive UDFs and PII masking mechanisms to enforce field-level confidentiality and support compliance requirements for sensitive datasets. • Built middleware services enabling message-based communication between UI systems and Apache Spark applications for asynchronous workflow coordination. • Wrote optimized Spark SQL and Hive queries for large-scale data extraction, aggregation, and transformation workloads. -- 2 of 2 --