Data Engineer

Fasken•Toronto, ON

31d•$90,000 - $110,000•Remote

About The Position

Fasken is seeking a Data Engineer to join its growing Data Analytics & Engineering team. This role is ideal for a professional who is hands-on, detail-oriented, and passionate about building reliable, well-governed, and scalable data platforms. You will be responsible for designing, building, and maintaining data warehouses and lakehouses in Microsoft Fabric, developing robust data pipelines, ensuring ongoing data integrity, and supporting analytics and governance initiatives across the firm. This role requires strong collaboration skills, a governance-first mindset, and the ability to clearly communicate complex data issues to both technical and non-technical audiences.

Requirements

Bachelor’s degree in math, economics, statistics, engineering, computer science, or other quantitative field, or equivalent level of experience
4+ years of experience in data engineering or a closely related role
Strong experience with Microsoft Azure–based data platforms, including: Azure services, Microsoft Fabric, SQL Server Other equivalent platforms are also considered: AWS, Snowflake
Proficiency in SQL and Python for data transformation and pipeline development
Experience building and maintaining: Data warehouses and/or lakehouses Data pipelines and dataflows
Familiarity with Power BI and semantic modeling (sufficient to build and support functional reports)
Experience working with data governance, access control, and compliance requirements
Strong troubleshooting, communication, and collaboration skills
Microsoft Certification required (or candidate to obtain Certification within the first year)
Strong analytical and problem-solving skills
Ability to work in a Remote-first environment, where internal clients may be located in various geographical locations and timezones.
Excellent planning and organizational skills, ability to manage multiple files simultaneously and meet established deadlines
Professionalism, discretion and commitment to outstanding customer service
Autonomy and ability to deal with multiple stakeholders
Organizational skills, thoroughness and ability to manage priorities

Nice To Haves

Knowledge of the Elite 3E ERP is an asset

Responsibilities

Design, build, and maintain data warehouses and data lakehouses in Microsoft Fabric
Develop and support ETL/ELT pipelines, dataflows, and data ingestion processes
Use notebooks (Python, SQL) to transform, validate, and move data across platforms
Build and maintain semantic models to support analytics and reporting
Ensure data integrity, accuracy, and consistency throughout all transformations
Monitor daily data loads to ensure completeness, freshness, and integrity
Maintain and follow a regular operational checklist to monitor data infrastructure health
Build Power BI dashboards, reports and alerts to monitor data movement, quality, and system performance
Monitor and optimize data platform compute usage to ensure efficient performance and cost control
Troubleshoot and resolve data-related issues and business tickets in a timely manner
Act as a champion and ambassador for data governance, compliance, and ethical data usage
Adhere to strict requirements such as ethical walls, access segregation, and confidentiality controls
Participate in and lead data governance initiatives, including: Defining and standardizing data fields Data clean-up and quality improvement efforts
Set up and maintain secure access to data resources, leveraging Microsoft Entra ID groups and role-based access control
Perform regular production system closing procedures on month end and year end.
Collaborate closely with: Data analysts and senior analysts Data governance leadership Technology teams and business stakeholders
Translate data issues and limitations into clear, business-friendly language
Support ad hoc reporting and data requests from the business
Partner with stakeholders to identify pragmatic, compliant, and scalable data solutions
Document and or update processes and Standard Operating Procedures (SOP)
Experience using GitHub and DevOps practices for version control, collaboration, and deployments
Leverage Copilot and modern tooling to optimize Python and SQL code
Contribute to improving standards, documentation, and repeatable patterns across the data platform