Data Engineer

Bed Bath & Beyond•Toronto, ON

2d•CA$85,000 - CA$110,000

About The Position

We are seeking a versatile and highly motivated Data Engineer to join our data analytics and reporting team. This role is critical in bridging the gap between raw data and actionable business insights, while also contributing to the robustness and efficiency of our data infrastructure. The ideal candidate will possess strong SQL skills for ad-hoc analysis and reporting, proficiency in Power BI for dashboard development, and hands-on experience with Python for data extraction and loading processes within our data warehouse environment. The core focus of this role is designing and maintaining well-structured data models and robust transformation logic that serve as the foundation for reliable, scalable analytics.

Requirements

Bachelor's degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
2–4 years of experience in a data-focused role, with a strong emphasis on data engineering and/or analytics.
Demonstrated experience designing dimensional models (star/snowflake schemas) and translating business requirements into logical and physical data models.
Advanced SQL proficiency within a modeling and transformation context (e.g., layered CTEs, reusable views, incremental logic).
Hands-on experience building pipelines that clean, standardize, and reshape raw data into analytics-ready datasets using SQL and/or Python.
Practical experience with dbt for modular, tested, and version-controlled transformation logic.
Experience developing and publishing interactive dashboards in Power BI or comparable tools such as Tableau or Looker.
Familiarity with workflow orchestration tools such as Apache Airflow.
Experience with cloud-based data platforms, particularly Google BigQuery or Azure Synapse Analytics.
Proficiency with Power BI report development and DAX formula creation.
Industry experience in e-Commerce, particularly with Shopify.
Solid experience with Python for data manipulation, scripting, and building ETL/ELT processes (e.g., Pandas, SQLAlchemy).
Strong analytical, problem-solving, and critical thinking abilities with keen attention to detail.
Excellent verbal and written communication skills, with the ability to explain complex data concepts to non-technical stakeholders.

Responsibilities

Design and implement dimensional and relational data models (star/snowflake schemas) that support scalable, performant analytics across business domains.
Develop, document, and maintain transformation logic that converts raw source data into clean, conformed, and business-ready datasets.
Write and optimize complex SQL queries and dbt models for data manipulation, aggregation, and layered transformation within the data warehouse.
Define and enforce data standards, naming conventions, and modeling best practices to ensure consistency across the warehouse.
Collaborate with stakeholders to translate business logic into well-structured data models that are intuitive and reusable.
Evaluate and refine existing models over time as business needs evolve, ensuring models remain accurate, efficient, and well-documented.
Design, develop, and maintain Python scripts for extracting and loading data from various source systems into our data warehouse.
Ensure data quality, accuracy, and consistency throughout the pipeline, from ingestion through to reporting-ready layers.
Identify and resolve data pipeline issues, ensuring timely and reliable data availability.
Contribute to the documentation of ETL processes, pipeline architecture, and data definitions.
Develop, maintain, and optimize interactive dashboards and reports using Power BI to visualize KPIs and business trends, built on top of well-modeled data layers.
Perform ad-hoc data analysis using SQL and collaborate with stakeholders across Marketing, Sales, Product, and Operations to translate business questions into clear, actionable insights.