Data Engineer

Toronto, ON, Canada
Full Time
Mid Level
The Data Engineer will play a key role in building and maintaining a modern data infrastructure. They will design, develop, and optimize ELT/ETL pipelines and implement efficient data models to support analytics, reporting, and business decision-making. The role involves deep collaboration with cross-functional teams to deliver scalable and high-performing data solutions using tools such as Snowflake, ADF, dbt, and Python. 

Responsibilities include:
  • Design, build, and maintain scalable and robust data pipelines using ELT/ETL patterns to ingest, transform, and integrate data.
  • Architect and implement efficient data models using Star, Snowflake, and One Wide Table (OWD) design patterns.
  • Maintain and create documentation of data architecture, data pipelines, and processes to ensure transparency and reproducibility.
  • Integrate data from multiple sources including databases, APIs, and third-party platforms using tools like Azure Data Factory (ADF) and dbt.
  • Lead technical discussions, advocate for best practices, and ensure solid data foundations and high standards in data engineering workflows.
  • Optimize data systems for performance and cost efficiency using partitioning, clustering, caching, indexing, and fine-tuning techniques.
  • Perform QA audits, manage data loads, generate memo files, and handle ad hoc data requests to ensure data integrity and reliability.
  • Support analytics and reporting by developing reusable metrics, dashboards, and self-service tools in Power BI and/or Sisense.
  • Enhance SDLC by incorporating CI/CD pipelines, version control (e.g., Git), and continuous improvement practices into data engineering processes.
  • Collaborate with internal and external stakeholders to gather requirements and deliver comprehensive data solutions.
Education: 

  • Bachelor’s Degree in Computer Science, Mathematics, Statistics, Finance, Information systems or equivalent related technical field experience 

Experience: 
  • 5+ years of professional experience in data engineering, data analytics, or a similar technical role.
  • Strong SQL skills with advanced knowledge of Joins, Unions, CTEs, Aggregations, Lag/Lead, and optimization techniques.
  • Proficiency in Python for data manipulation, scripting, and automation.
  • Experience working with Snowflake, dbt, and Azure Data Factory (ADF).
  • Demonstrated experience in data modeling, including dimensional and modern approaches (Star, Snowflake, OWD).
  • Hands-on experience in building and maintaining data pipelines (ETL/ELT).
  • Understanding of cost optimization, caching, partitioning, and indexing strategies for performance tuning.
  • Familiarity with BI tools such as Power BI, Sisense, Looker, Tableau, and Domo.
  • Experience with customer personalization solutions and handling large datasets.
  • Exposure to scripting languages like Python, Perl, or Shell.

Tools & Skills: 

  • Deep understanding of complex SQL and Snowflake SQL syntax, including Time Travel, Streams, Cloning, and Role-Based Access.
  • Strong knowledge of Snowflake, Azure Data Factory, and dbt.
  • Experience with version control systems and CI/CD workflows.
  • Knowledge of DataBricks (ADB preferred) and ability to interpret existing solutions.
  • Familiarity with reporting tools, especially Power BI and/or Sisense.
  • Advanced proficiency in Python and Excel for data analysis and transformation.
  • Understanding of data warehousing, proactive data quality monitoring, and structured/unstructured data formats including JSON.
Key Competencies: 
  • Proven problem-solving skills and high attention to detail.
  • Ability to partner with business stakeholders to define questions and build data sets to answer them.
  • Capable of navigating ambiguity and balancing multiple priorities in a fast-paced environment.
  • Excellent communication and presentation skills for technical and non-technical audiences.
  • Self-starter with a spirit of innovation and consistent delivery.
  • Demonstrated ability to work collaboratively in multi-disciplinary teams and produce results quickly.
Assets:
  • Experience in Telecom or banking industries, especially related to data collection or retention.
  • Hands-on experience with ADF data transformations for custom reporting models.
  • Experience in scripting and automation using Python, Perl, or Shell.
  • Familiarity with data transformations using tools like dbt.
  • Data analysis, report development, and business analysis
  • Experience with tools like Looker, Excel, Power BI, Tableau, R, SAS
Share

Apply for this position

Required*
We've received your resume. Click here to update it.
Attach resume or Paste resume
Attach resume as .pdf, .doc, .docx, .odt, .txt, or .rtf (limit 5MB) or Paste resume

Paste your resume here or Attach resume file

To comply with government Equal Employment Opportunity and/or Affirmative Action reporting regulations, we are requesting (but NOT requiring) that you enter this personal data. This information will not be used in connection with any employment decisions, and will be used solely as permitted by state and federal law. Your voluntary cooperation would be appreciated. Learn more.
Human Check*