Data Scientist - Data Analytics and Infrastructure

Job description

We are looking for Data Scientists passionate about Data Analytics and Infrastructure, with strong foundations in data engineering, analytics, and statistics. You should enjoy working with large, complex datasets and developing efficient pipelines that enable scalable, reliable data analytics. You’ll be responsible for designing and maintaining data infrastructure, automating workflows, and enabling data accessibility across teams. Your work will directly impact business decisions by delivering high-quality insights and building robust analytics systems. Strong problem-solving, communication, and collaboration skills are key for this role. BS (or higher, e.g., MS, or PhD) in Computer Science, Data Engineering, or a related technical field Experience building and maintaining data pipelines and infrastructure in production environments Proficient in SQL and data wrangling at scale (e.g., Spark, Airflow, dbt, etc.) Strong grasp of statistics, data modeling, and performance tuning Skilled in Python (Pandas, Numpy, etc.) and data visualization tools (e.g., Tableau, Power BI) Familiarity with cloud data platforms (e.g., AWS, GCP, Azure) Ability to design data schemas and implement analytics tracking strategies Analytical mindset with a focus on impact, efficiency, and scalability We have competitive compensation. Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management. You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.