Data Engineer - Big Data

Role: Data Engineer

Location: Toronto, ON

Duration: Full Time

"Responsibilities

Design, develop, and maintain data processing pipelines using Apache Spark.

Collaborate with data engineers, data scientists, and business analysts to understand data requirements and deliver solutions that meet business needs.

Write efficient Spark code to process, transform, and analyze large datasets.

Optimize Spark jobs for performance, scalability, and resource utilization.

Integrate Hadoop, Hive, Spring, Hibernate, Kafka, and ETL processes into Spark applications.

Troubleshoot and resolve issues related to data pipelines and Spark applications.

Monitor and manage Spark clusters to ensure high availability and reliability.

Implement data quality and validation processes to ensure accuracy and consistency of data.

Stay up-to-date with industry trends and best practices related to Spark, big data technologies, Python, and AWS services.

Document technical designs, processes, and procedures related to Spark development.

Provide technical guidance and mentorship to junior developers on Spark-related projects.

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Proven experience (10+ years) as a Spark Developer or in a similar role working with big data technologies.

Strong proficiency in Apache Spark, including Spark SQL, Spark Streaming, and Spark MLlib.

Proficiency in programming languages such as Scala or Python for Spark development.

Experience with data processing and ETL concepts, data warehousing, and data modeling.

Solid understanding of distributed computing principles and cluster management."