Junior Analytics Engineer
2h ago⚠️ Before applying, please carefully review all the job requirements
- Location:
- Canada
- Experience:
- 1–2+ years of experience in analytics, data engineering, or a related quantitative field
- Job Type:
- Full-time
- Company:
- Top Hat
Job OverviewThis position offers an entry-to-intermediate opportunity within the Business Analytics group at Top Hat, focusing on data infrastructure reliability, reporting pipeline maintenance, and analytics delivery. Operating within Corporate Operations, the successful candidate will work alongside senior engineers to transform complex operational requirements into optimized SQL models and reliable data workflows. The role heavily leverages core data stack tools and practices including SQL, Python, Business Intelligence platforms, dbt, Airflow, and Git version control. This position is ideal for early-career data professionals who combine a solid quantitative foundation with a desire to adopt modern software engineering practices while directly supporting cross-functional business units like Revenue, Finance, Customer Success, and Marketing.
Important InformationApplicants should carefully review the latest job requirements and application instructions
Key Responsibilities
- Design, refine, and support data models to uphold high standards of data accuracy and pipeline dependability.
- Oversee active data workflows to spot, diagnose, and fix operational errors and inconsistencies.
- Collaborate with senior team members to translate business logic into performant, clean SQL logic.
- Construct, update, and document internal reporting dashboards while resolving visualization and data inaccuracies.
- Perform routine data validation checks and respond to ad-hoc analytical inquiries from business partners.
- Integrate core software engineering principles into data management, including version control workflows and test automation.
Required Skills and Qualifications
- 1 to 2+ years of relevant experience in quantitative roles such as data analytics or data engineering.
- Bachelor's degree in Computer Science, Engineering, Statistics, or an equivalent practical background.
- Proficiency in advanced SQL features, including CTEs, window functions, and query performance tuning.
- Working competency with Python for data manipulation and scripting.
- Practical exposure to data modeling concepts and Business Intelligence platforms such as Looker or Tableau.
- Strong desire to work with modern data stack tools including dbt and Airflow, alongside standard software tooling like Git and automated testing.
- Analytical mindset with strong attention to detail and a collaborative problem-solving approach.
- Prior experience within tech startups or software companies is considered a plus.
- Prior experience in higher education as an instructor or student is beneficial.
Who Should ApplyThis role is well-suited for early-career analytics professionals, data engineers, or quantitative analysts looking to refine their technical skillset within an established ed-tech environment. Candidates who possess a strong command of SQL and Python, combined with an eagerness to master modern data tools like dbt and Airflow, will find this position compelling. If you enjoy working collaboratively to solve technical data challenges, care deeply about data hygiene, and thrive in a remote-first work model that supports internal business operations, this opportunity aligns well with your professional background.
What the Company Offers
- Flexible, remote-first work setup with access to a Toronto headquarters.
- Health coverage starting on day one of employment.
- Paid time off policy structured to support personal wellbeing and self-care.
- Continuous professional learning and development opportunities across all levels.
- Exposure to modern technologies, including generative AI applications.
Application TipsWhen applying for this role, tailor your resume to emphasize strong core SQL capabilities—specifically highlighting projects involving complex queries, window functions, and performance optimization. Include explicit examples of data pipelines, dashboard builds, or data modeling projects you have contributed to, noting any tools used such as Python, Looker, Tableau, dbt, or Git. If you have past exposure to technology startups or background experience in higher education, be sure to highlight these connections to demonstrate alignment with Top Hat's core focus area.
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