Java ‑Stack Developer; Microservices, Big Data & Spark Batch

Role Overview

A highly experienced Java Full‑Stack Engineer with deep expertise in Microservices, distributed systems, and Big Data platforms. This role requires hands-on design and development of high‑throughput microservices, Spark‑based batch pipelines, and Kafka‑driven streaming workflows for large‑scale enterprise environments.

• Design microservices using Java, Spring Boot, Spring Cloud, and cloud‑native patterns.
• Build and optimize REST APIs
  , event‑driven components, and distributed workflows.
• Develop Spark batch jobs for large‑scale data processing, transformations, and aggregations.
• Implement Kafka streaming pipelines for real‑time ingestion and processing.
• Build full‑stack features using React/Angular (or client‑specified UI stack).
• Optimize performance of microservices and data pipelines for low latency and high throughput
  .
• Collaborate with Dev Ops teams to deploy services on AWS/GCP/Azure.
• Ensure observability, fault tolerance, and reliability across services.
• Lead code reviews, mentor junior engineers, and enforce engineering best practices.

• Java (8/11/17), Collections, Concurrency, Multithreading
• Spring Boot, Spring Cloud, REST, Microservices
• Spark (Batch + Structured Streaming)
• Hadoop ecosystem:
  Hive, HDFS, HBase, Presto (as applicable)
• Front‑end:
  React / Angular
• Cloud: AWS preferred (EMR, EKS, Lambda, S3, DynamoDB, Fargate)
• CI/CD:
  Jenkins, Git Hub Actions, Maven/Gradle

• 10+ years of enterprise‑grade development experience.
• Strong experience building Spark batch pipelines for large datasets.
• Proven ability to design distributed, event‑driven microservices
  .
• Hands‑on experience with Kafka streaming and high‑volume ingestion.
• Solid understanding of system design
  , scalability, and performance tuning.
• Experience leading teams, mentoring developers, and driving architectural decisions.