J&M GroupVerified Job Source

Data Engineer

Toronto, ON
On-site
Posted Sep 8, 2026
1 position

Opens an external site

Employment type: Full-time
Experience level: Mid-level · 2+ years
Apply by: Mar 7, 2027
Posting language: English
Working hours: 40 hours per week
Seniority: Entry level
Application method: Direct apply is available

Job summary

Design, develop, and optimize scalable data pipelines and real-time processing solutions using PySpark, Spark, and Kafka. Collaborate with cross-functional teams to implement ETL/ELT workflows and ensure data quality and governance.

Job details

An experienced Data Engineer with strong expertise in Big Data technologies to design, develop, and support enterprise-scale data platforms. The ideal candidate should possess hands-on experience in PySpark, Apache Spark, Kafka, Hadoop ecosystem components, and Apache NiFi, with a strong understanding of data ingestion, transformation, and real-time processing frameworks. Key Responsibilities Design, develop, and optimize scalable data pipelines using PySpark, Spark, Hadoop, and Apache NiFi. Build and maintain batch and real-time data processing solutions. Develop and support Kafka-based streaming applications and event-driven architectures. Create and optimize ETL/ELT workflows for large-scale structured and unstructured datasets. Develop complex SQL queries for data extraction, transformation, validation, and troubleshooting. Implement data ingestion solutions from databases, APIs, files, and streaming sources. Monitor, troubleshoot, and enhance the performance of Spark jobs and data pipelines. Collaborate with architects, business analysts, and development teams to deliver high-quality data solutions. Support platform upgrades, deployments, testing, certification, and production releases. Ensure data quality, governance, security, and operational excellence across data platforms. Mandatory Skills PySpark Apache Spark (Spark SQL, DataFrames) Apache Kafka Hadoop Ecosystem (HDFS, Hive, YARN) Apache NiFi SQL Python Preferred Skills Spark Streaming Airflow / Oozie Hive Scala Jenkins, Bitbucket, Git JIRA, Confluence Cloud Platforms (GCP/AWS/Azure) Data Warehousing concepts and Dimensional Modeling

What you’ll do

Requirements

Requires strong expertise in Big Data technologies including the Hadoop ecosystem, Apache NiFi, and Python. Candidates should be proficient in SQL and experienced in building event-driven architectures and data ingestion solutions.