Java Big Data Engineer

Aarorn Technologies Inc.•Toronto, ON

1d•Hybrid

About The Position

We are looking for an experienced Java Big Data Engineer to join a dynamic team in the financial services sector. This is a hybrid role based in Toronto, requiring 4 days onsite per week. You will work on large-scale data processing pipelines, real-time streaming solutions, and high-performance Java applications.

Requirements

Strong core Java (8+) development experience
Hands-on experience with Apache Spark (batch and streaming)
Proficiency in Hadoop ecosystem (HDFS, Hive, YARN)
Experience with Kafka for real-time data streaming
Strong SQL skills and experience with relational and NoSQL databases
Experience with Unix/Linux environments and shell scripting
Familiarity with version control (Git) and CI/CD pipelines

Nice To Haves

Experience with Azure (Data Lake, Databricks, Synapse) or AWS (EMR, S3, Redshift)
Knowledge of Scala or Python
Understanding of containerization (Docker, Kubernetes)
Experience with scheduling tools (Airflow, Oozie)
Financial services or banking domain experience
Knowledge of data warehousing concepts and tools

Responsibilities

Design, develop, and maintain scalable big data pipelines using Java and Spark
Work with Hadoop ecosystems (HDFS, Hive, HBase) to process and store large volumes of data
Implement real-time streaming solutions using Kafka and Spark Streaming
Optimize and tune performance of big data applications for efficiency and reliability
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements
Write clean, maintainable, and testable code following best practices
Participate in code reviews, design discussions, and agile ceremonies
Troubleshoot and resolve production issues related to data processing and integration
Ensure data quality, governance, and security standards are met
Work with cloud-based data platforms (preferably Azure or AWS)
Support and maintain existing big data workflows and ETL processes