Java Developer

Position: Java Developer

Location: : Montreal Quebec , Canada (Onsite)

Job type: Fulltime

Job Summary

We are seeking a highly skilled Java Spark Developer with strong experience in designing and developing large-scale distributed data processing applications. The ideal candidate will have expertise in Java, Apache Spark, Hadoop ecosystem, SQL, and Cloud technologies (AWS/Azure/GCP). The candidate will be responsible for building scalable data pipelines, optimizing Spark applications, and collaborating with cross-functional teams to deliver high-performance data solutions.

Key Responsibilities

• Design, develop, and maintain scalable big data applications using Java and Apache Spark.
• Build and optimize batch and real-time data processing pipelines.
• Develop Spark applications using Spark Core, Spark SQL, DataFrames, and Spark Streaming.
• Work with large datasets stored in HDFS, Hive, S3, Delta Lake, or Snowflake.
• Implement data transformation, cleansing, and aggregation processes.
• Optimize Spark jobs for performance, memory utilization, and resource management.
• Develop REST APIs and microservices using Spring Boot where required.
• Collaborate with Data Engineers, Architects, Business Analysts, and DevOps teams.
• Troubleshoot production issues and perform root cause analysis.
• Implement CI/CD pipelines and automated deployment processes.
• Ensure data quality, security, and compliance with enterprise standards.
• Participate in code reviews and follow best coding practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, or related field.
• 5+ years of Java development experience.
• 3+ years of hands-on Apache Spark experience.
• Strong proficiency in:
• Java 8/11/17
• Apache Spark
• Spark SQL
• Hadoop Ecosystem (HDFS, Hive)
• SQL and Database Development
• Experience with:
• Spring Boot and Microservices
• Kafka or other messaging platforms
• RESTful APIs
• Git, Maven, Jenkins
• Linux/Unix environments
• Strong understanding of distributed computing concepts.
• Experience tuning and optimizing Spark jobs.

Preferred Qualifications

• Experience with cloud platforms:
• AWS (EMR, S3, Glue, Lambda)
• Azure Databricks
• Google Cloud Dataproc
• Experience with:
• Databricks
• Delta Lake
• Snowflake
• Airflow
• Kubernetes and Docker
• Exposure to Scala or Python.
• Banking, Financial Services, Insurance, Retail, or E-commerce domain experience.

Technical Skills

Programming Languages

• Java
• SQL
• Python (Preferred)
• Scala (Preferred)

Big Data Technologies

• Apache Spark
• Spark SQL
• Spark Streaming
• Hadoop
• Hive

Cloud & Data Platforms

• AWS EMR
• Databricks
• Snowflake
• Delta Lake

DevOps & Tools

• Git
• Jenkins
• Maven
• Docker
• Kubernetes

Nice to Have

• Experience with real-time streaming using Kafka and Spark Streaming.
• Knowledge of Data Lake and Lakehouse architectures.
• Experience implementing data governance and monitoring solutions.
• Familiarity with Agile/Scrum methodologies.