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.
- Solid 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.

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