Senior Data Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in Canada. Join a forward-thinking digital entertainment team building data-driven products across sports media, online gaming, and interactive entertainment. As a Senior Data Engineer, you will play a key role in transforming complex datasets into reliable, actionable insights that support strategic and operational decisions. You will collaborate with data engineers, analysts, and business stakeholders to develop scalable pipelines and improve the quality and accessibility of data across the organization. Using technologies such as SQL, dbt, BigQuery, Airflow, and Python, you will help build robust data models and streamline data workflows. You will also contribute to analytical best practices, mentor colleagues, and help expand the adoption of modern data exploration tools. This is an exciting opportunity to combine technical expertise, business impact, and an interest in sports and digital consumer experiences within a collaborative, fast-paced environment. Accountabilities - Develop and optimize data pipelines: Build, maintain, and improve data transformation workflows that deliver accurate, reliable, and well-structured datasets to meet business and analytical requirements. - Create and maintain data models: Apply advanced SQL skills to develop, test, and optimize dbt models, ensuring data consistency, quality, and usability across multiple business functions. - Manage workflow orchestration: Configure and maintain Airflow tasks and schedules, monitor pipeline execution, troubleshoot failures, and improve the reliability of data processing operations. - Collaborate with stakeholders: Work closely with business teams to identify data-driven opportunities, clarify requirements, prioritize projects, and align technical solutions with organizational objectives.

- Support data engineering initiatives: Partner with fellow engineers to design and implement data pipelines, resolve technical challenges, and improve the efficiency of data infrastructure. - Deliver actionable insights: Conduct data analyses, interpret findings, and present clear recommendations to business stakeholders to support informed decision-making. - Ensure analytical quality: Review team analyses and data models to verify accuracy, reliability, and clarity before insights are shared with stakeholders. - Promote data accessibility: Support the implementation and adoption of data exploration tools, helping teams access, understand, and use data more effectively. - Mentor and develop team members: Contribute to recruitment, onboarding, knowledge sharing, and professional development while helping colleagues strengthen their technical and analytical capabilities. - Drive continuous improvement: Identify opportunities to enhance data processes, resolve recurring issues, and establish practical engineering standards in a dynamic environment. - Support additional priorities: Take on other responsibilities as needed to support the team's evolving objectives. Requirements - Education: A university degree in Computer Science, Statistics, Business, or a related discipline. - Professional experience: At least 4 years of experience in data engineering or analytics engineering, with a demonstrated ability to deliver dependable data solutions. - Technical expertise: Hands-on experience with BigQuery, dbt, Airflow, Python, and relational databases. - SQL proficiency: Strong SQL skills and experience developing, maintaining, and optimizing data transformation pipelines and analytical data models. - Data workflow management: Familiarity with orchestrating scheduled data workflows, troubleshooting pipeline issues, and maintaining data quality.