Senior Data Engineer

As a Sr. Data Engineer within the D2L Data Services team under IT, you will contribute to expanding and maintaining our data pipeline architecture to democratize data at D2L. You will apply your experience working with various data technologies to make data accessible in a consistent manner across the organization. In this role, you will be responsible for building and maintaining services to extract, transform and load data from several data sources leveraging a technology stack influenced by the Data Services team.

HOW WILL I MAKE AN IMPACT?

• Collaborate with the D2L Data Services team lead to streamline and prioritize daily data operations and maintenance activities 
• Contribute to the evolution of data practices within D2L. 
• Contribute to creating, maintaining and operationalizing a sustainable data pipeline architecture 
• Develop data extractions and tools for processing and storing data while ensuring the scalability, efficiency, and reliability of our data infrastructure aligned to common practices 
• Ensure that D2L’s corporate data is secure and aligned with contractual obligations for data residency 
• Build and support paved paths for data sets to be used consistently by the distributed visualization functions across D2L 
• Collaborate with business stakeholders to understand functional requirements to enable data-driven decision-making through simple self-service reporting 
• Engage with Visualization experts to provide consultation on optimizing data processes and efficiencies

WHAT IS D2L LOOKING FOR FROM ME?

Competencies: 

• An analytical mind, demonstrating creativity, problem-solving aptitude, and a desire for continual improvement.  
• 4+ years of experience in data engineering, data science, or a related field, showcasing your knowledge and proven track record. Development experience (ex. Python) is an asset. 
• Hands-on experience with database design, and complex SQL queries enabling you to create effective data solutions. 
• Familiarity with deploying AWS infrastructure using Terraform, and experience working with ETL systems such as SSIS, Glue, or similar tools. 
• Build and manage data lakes, warehouses, and vector databases that support LLMs and generative AI use cases 
• Passion for AI technologies and experience integrating AI/ML models or platforms.   
• Experience working collaboratively with business stakeholders on designing and developing data-driven insights. 
• Effects quantifiable business impact by solving stakeholder problems using data solutions and influencing outcomes based on best practices.   

Education Recommendations:

• Education in Computer Science, Data Science, Engineering, or relevant experience