Permanent and on-site position in Ottawa

We are seeking a Data Engineer to join our client's team. You will collaborating closely with the Data Architect and AI teams to design and implement data integration strategies, build data pipelines, create data models, establish governance practices, and plan scalable data solutions. Working with various departments, you will manage and unify data from multiple sources, supporting the organization’s data management and analytics objectives.

Key Responsibilities:

• Partner with the Data Architect and technical teams to design and deliver effective data integration solutions.
• Build, maintain, and enhance our data infrastructure and pipeline systems.
• Develop and manage data pipelines using technologies like Apache Spark, Azure Data Factory, and other relevant tools.
• Create structured datasets for analytics and reporting, including dimensional modeling.
• Uphold data governance standards to ensure data quality, integrity, and industry compliance.
• Plan and deploy scalable data solutions on cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• Work with various business units to understand data needs and deliver tailored data solutions.
• Apply best practices for data security and ensure compliance with data privacy regulations (e.g., GDPR, CCPA).
• Operate within an Agile environment, collaborating with cross-functional teams and using project management tools to meet project milestones effectively.

Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, or a related field; a Master’s degree or relevant certifications is a plus.
• 5 + years of experience proven experience as a Data Engineer, ideally in a similar industry (e.g., waste management, material supply, construction).
• Expertise in SQL, Python, data integration, ETL processes, and data governance.
• Practical experience with cloud platforms (e.g., Microsoft Azure) and big data technologies (e.g., Hadoop, Apache Spark).
• Strong knowledge of data warehousing principles, data lake architecture, and dimensional modeling.