Data Engineer IV

OnX is a leading technology solution provider that serves businesses, healthcare organizations, and government agencies across Canada. OnX combines deep technical expertise with a full suite of flexible technology solutions—including Generative AI, Application Modernization, Managed Hybrid Cloud, Cybersecurity, Unified Communications, and Infrastructure solutions. From developing and deploying modern applications and the secure, scalable platforms on which they run, to managing, monitoring, and optimizing their operations, OnX delivers comprehensive technology solutions for its clients’ transformative business initiatives. For more information, please visit www.onx.com.

Overview

In today's rapidly evolving environment, organizations need to make data-driven decisions that deliver enterprise value. Our OnX Cloud and Artificial Intelligence practitioners design, develop, and implement large-scale data ecosystems, leveraging cloud-based platforms to integrate structured and unstructured data. We utilize automation, cognitive, and science-based techniques to manage data, predict scenarios, and prescribe actions. By continuously optimizing our cloud infrastructure and providing As-a-Service offerings, we ensure ongoing insights and improvements to enhance operational efficiency. We assist clients in transforming their businesses by developing organizational intelligence programs and strategies, enabling them to stay ahead in their markets.

Responsibilities

As a Data Engineer, you will:

• Design, develop, and implement comprehensive data pipelines using ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks to meet mission objectives.
• Collaborate with cross-functional teams to understand data requirements and design optimal data models and architectures.
• Optimize data pipelines for scalability, reliability, and high-performance processing, and provide innovative solutions to complex data-related challenges involving large datasets.
• Ensure data quality through validation processes and governance frameworks.
• Collaborate with data scientists to enable machine learning workflows.
  
  

Requirements

Required:

• 5-8 Years of Industry Experience
• Proficiency in ETL tools (e.g., Apache Airflow) and big data technologies (e.g., Spark). Familiarity with data engineering tools from major cloud platforms such as AWS Glue, AWS Redshift, Azure Data Factory, Azure Synapse Analytics, Google Cloud Dataflow, and Google BigQuery.
• Experience with cloud-native analytics platforms like Azure Fabric, Azure Synapse Analytics or Google BigQuery.
• Strong programming skills in Python or Scala for data processing tasks.
• Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
• Effective communication skills, written and oral
  
  

Nice To Have

• Certifications: Google Professional Data Engineer or AWS Certified Data Analytics.
  
  

Education

• Four years of College resulting in a Bachelor's Degree or equivalent Bachelor's in Business, Computer Science, Engineering, or related field
  
  

Due to U.S. Government requirements applicable to foreign-owned telecommunications providers, non-US citizens may be required to submit to an extensive government agency background check which will necessitate disclosure of sensitive Personally Identifiable Information.

The Pay Range For This Role Is

120,000 - 160,000 CAD per year(Remote - Toronto, CA)