Junior Analytics Engineer

We are looking for a Junior Analytics Engineer to help maintain data pipelines and surface key insights at Top Hat. You will be part of Business Analytics, a small but impactful data team serving our Operational teams (Revenue, Finance, Customer Success,Marketing, etc.), helping to ensure our data is trusted and ready to support the needs of Top Hat’s growth. You will: Develop, maintain, and optimize data models to ensure data integrity and pipeline reliability. Monitor data pipelines, identifying and resolving inconsistencies in existing processes. Learn our business, translating stakeholder requirements into clean, efficient SQL queries under the guidance of senior team members. Build, document, and maintain internal dashboards; troubleshooting issues to ensure accurate reporting. Assist with ad-hoc data requests and perform data quality checks. Apply software engineering best practices, including version control and automated testing. About you: 1-2+ years of experience in analytics, data engineering, or similar quantitative work. Degree in Computer Science, Statistics, Engineering or equivalent practical experience. Solid foundation in SQL (CTEs, window functions, query optimization) and Python. Familiarity with data modeling and Business Intelligence tools (e.g., Looker, Tableau). Eagerness to learn and apply modern data tools (dbt, Airflow) and software engineering best practices (Git, testing). Detail-oriented, with a drive to solve technical problems in collaborative, hands-on settings. Bonus points for: Experience working in tech products, particularly in startups. Recent experience in higher ed as a teacher or student. Why team members love working at Top Hat: A noble mission that creates meaningful, fulfilling work A team that cares deeply for customers and for each other Flexible, remote first work environment Professional learning and development for all role levels An awesome and welcoming Toronto HQ Competitive health benefits that start on day one A management team focused on performance, growth, engagement and connection Our winning strategy and market potential Innovative PTO policy with lots of time and space for self-care Passionate customers that believe in us—and what we do A chance to work with new tech like generative AI—and see the customer impact

You will develop, maintain, and optimize data models while ensuring the reliability of data pipelines. Additionally, you will translate stakeholder requirements into efficient SQL queries and build internal dashboards to support operational teams.

Candidates should have 1-2+ years of experience in analytics or data engineering and a degree in a quantitative field. A solid foundation in SQL and Python is required, along with familiarity with data modeling and BI tools.

• Flexible remote first work environment • Professional learning and development • Competitive health benefits • Innovative PTO policy

• SQLSouhaitée
• TableauSouhaitée
• Tests automatisésSouhaitée
• GitSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• SQL
• Python
• Data modeling
• Looker
• Tableau
• dbt
• Airflow
• Git
• Data pipelines
• Business intelligence
• Software engineering
• Data integrity
• Dashboarding
• Troubleshooting
• Automated testing
• Market Potential
• Stakeholder Requirements
• Customer Success Management
• Apache Airflow
• Git (Version Control System)
• Willingness To Learn
• Test Automation
• Business Analytics
• Dashboard
• Business Intelligence Tools
• Management
• Version Control
• Computer Science
• Data Engineering
• Data Integrity
• Data Modeling
• Data Quality
• Finance
• Marketing
• Innovation
• Python (Programming Language)
• Query Optimization
• Software Engineering
• SQL (Programming Language)
• Statistics
• Tableau (Business Intelligence Software)
• Troubleshooting (Problem Solving)
• Window Function
• Detail Oriented
• Looker Analytics
• Data Pipelines

• Data & Analytics
• Technology
• Software
• Engineering
• Analytics Engineer
• Data Scientist
• Systems Analysts
• Data Scientists

Formation minimale

Baccalauréat

Expérience minimale

0+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Exigences de lieu

Country, Canada