Data Engineer

Job Description Job Description Data Engineer, DE 103025 Department : Information Systems Type of Position : Full Time, Permanent Location : 7th Floor, 5160 Yonge Street, Toronto, ON Reporting to : Manager, Digital Analytics Work Model : Hybrid flexible work schedule (All remote work must be completed from your home office within the province of Ontario.) About Tarion Since 1976, Tarion has served new home buyers and new homeowners by ensuring that one of their life's biggest investments is protected. Almost every new home in the province is covered by a new home warranty. This warranty protection is provided by Ontario's builders and lasts up to seven years. It is backstopped by Tarion. More than 375,000 homes are currently enrolled in the warranty program. Every year about 55,000 new homes are enrolled. How We Make a Difference A home is one of life's biggest purchases. As an independent, not‑for‑profit organization, Tarion provides Ontario's new home buyers and owners with peace of mind that their purchase is safeguarded through the province's new home warranty and protection program. Almost every new home in the province is covered by a new home warranty. Tarion ensures consumer protection by providing free tools, guides and resources to help homeowners understand their builder's warranty and navigate warranty claims with confidence. If a builder does not meet their warranty commitments, Tarion offers guidance to help homeowners ensure they receive the coverage they're entitled to, and when necessary, steps in to help resolve warranty claims. About the Role The Data Engineer will contribute their expertise to Tarion's newly formed digital analytics team while growing with the evolving strategic direction. They will be focused on building and managing ETL pipelines while supporting the development of cloud‑native AI / ML solutions by designing, testing, implementing, and maintaining data engineering solutions. The Data Engineer will work with Tarion's Application Development and Infrastructure teams, business users, external vendors and IT partners to support our ongoing initiatives. This is a hybrid role requiring working two (2) days in the office and three (3) days remotely, per week. (All remote work must be completed from your home office within the province of Ontario.) What you will be doing Design, build and support the data and ETL pipelines that incorporate Tarion's AI governance framework. Design logical and physical data models for warehouse, and establish guidelines to ensure consistency, quality and completeness of data assets. Collaborate with Application owners, data architects, data scientists and other SMEs to design scalable data infrastructure required to support AI / ML solutions. Integrate new data management technologies and software engineering tools into existing structures to support Analytics and AI use cases Handle the performance tuning of data loads and databases Identify, analyze and interpret trends or patterns in complex data sets Ensure reliable execution and monitoring of nightly data pipeline jobs, including troubleshooting failures, optimizing performance, and maintaining data integrity across systems Liaise with the Release Lead to implement, monitor and improve the MLOps process within an Agile framework. Translate business needs into data model strategies with the support of SMEs Incorporate core data management competencies including data governance, data security and data quality. Design AI‑ready ecosystems that are flexible, scalable and resilient, supporting both structured and unstructured data for Machine learning and AI use cases Assist in the design and development of databases and data marts. Provide technical assistance in identifying, evaluating, and developing systems and procedures. Establish and enforce guidelines to ensure consistency, quality, and completeness of data assets Coordinate with data source application owners, business owners, and data users to better understand data and information needs. A great candidate for this position will have A minimum of 3 years of hands‑on experience with data engineering and MLOps. Bachelor's degree in Computer Science, Engineering or a related field. Strong programming skills in languages such as Python, Java, or Scala. Knowledge of AI / ML frameworks such as Tensor flow, Pytorch, or MLflow Understanding of generative AI and advanced analytics approaches, as AI increasingly influences end to end data workflows Proficiency in SQL and experience with relational database systems (e.g., MS SQL Server). Experience with cloud platforms (e.g., AWS, Azure) and their data services. Experience with data modeling, ETL development, and data warehousing solutions. Ability to work independently and collaboratively with cross‑functional teams. Ability to work outside core hours to meeting project or operational objectives and deadline. Strong written and verbal communication skills. Why Choose Tarion? We believe that Tarion's employees are its most valuable asset. We strive to provide a welcoming work environment. We offer employees a competitive compensation program, opportunities for learning and development, an employee discount program, access to wellness programs, and a variety of Employee Assistance Program tools and online resources to support well‑being. At Tarion, we believe that a strong commitment to diversity and inclusion allows employees to perform at their very best and underpins a culture in which everyone feels they have an equal opportunity to belong and build a career. Tarion is committed to developing and maintaining work environments and practices that ensure equality of opportunity in recruitment, selection and promotion, and to removing systemic barriers so that employees have every opportunity to feel included in the workplace. If you are a person with a disability and have questions or would like help with your application, please contact a member of the Human Resources Department. Application Submissions & Deadline Please submit a single file with a covering letter and resume with vacancy code DE 103025 , by no later than November 14, 2025 . #J-18808-Ljbffr