Full Stack Java Developer

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Java
Hadoop
Hive
Spark
HDFS
AWS clouD
ETL

Job Details

Title: Full Stack Java Developer Location: Iselin, NJ (Hybrid 3 days onsite) Duration: 12+ Months Contract W2 Role

Job Description

We are seeking an experienced Full Stack Java Developer with a strong emphasis on backend development, big data engineering, and AWS cloud technologies. In this role, you will design, build, and optimize high-performance backend services and large-scale data processing pipelines within a fast-paced financial domain environment.

The ideal candidate will have hands-on expertise with Java, Hadoop/Spark ecosystems, ETL frameworks, and AWS services, along with the ability to work on both development and data engineering initiatives. You will collaborate with cross-functional teams to deliver scalable, secure, and robust data solutions that support enterprise-level applications and analytics platforms.

Key Responsibilities

  • Develop and enhance backend services using Java, ensuring scalability, security, and performance.
  • Design and implement big data pipelines leveraging Hadoop, Spark, Hive, and distributed processing frameworks.
  • Build and maintain ETL/ELT workflows using AWS Glue, PySpark, Databricks, and related cloud-native tools.
  • Work with structured and unstructured data to build data models, transformation logic, and processing workflows.
  • Implement real-time and batch data integration solutions using Kafka, data lakes, and cloud platforms.
  • Deploy and monitor data and application workloads on AWS (S3, Lambda, Redshift, CloudWatch).
  • Collaborate with DevOps teams to automate CI/CD pipelines using Jenkins, Git, Autosys, and Airflow.
  • Troubleshoot production issues, optimize performance, and ensure reliability of data and application systems.
  • Participate in code reviews, architectural discussions, and design documentation.

Ideal Candidate Profile

  • Strong backend Java development background.
  • Deep knowledge of the big data ecosystem including Hadoop, Hive, Spark, HDFS.
  • Experience building and running workloads on AWS cloud.
  • Proven experience creating data pipelines, handling large datasets, and supporting enterprise ETL workflows.
  • Solid understanding of data modeling, transformations, and performance tuning.
  • Ability to work effectively in a hybrid onsite/remote environment.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Black Rock Group