Lead Data Engineer
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Before you apply
SalaryCA$130k – CA$150k
LocationToronto, Canada
Typefull-time
SeniorityLead
DepartmentTechnology
Company size5+ people
First seenOct 18, 2026 · 2w ago
Verified live11h ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field
Experience with any programming language (e.g., Python, Scala)
Familiarity with foundational data concepts (e.g., ETL/ELT, data warehousing, data modeling)
Basic understanding of SQL and relational databases
Exposure to cloud platforms (preferably Azure)
Eagerness to learn and develop skills in Snowflake, Azure, and DBT
Strong problem-solving skills and attention to detail
Excellent communication and collaboration skills
Ability to work independently and as part of a team
Prior experience or hands-on projects utilizing Snowflake
Hands-on experience with GenAI coding tools and agents (e.g., Cursor, Claude Code, Cortex Code)
Prior coursework or projects involving data engineering concepts
Familiarity with version control systems (e.g., Git)
Understanding of data visualization tools (e.g., Power BI)
Certifications related to Azure, Snowflake, or data engineering
Skills
Python
Scala
SQL
Snowflake
Azure
Azure Data Factory
Azure Data Lake Storage
DBT
Git
Power BI
GenAI tools
About the role
We are looking for a Data Engineer who will play a key role in building, maintaining, and optimizing our data pipelines and infrastructure. You will work closely with data scientists, analysts, and other engineers to ensure the reliable and efficient flow of data across our systems. This role offers an opportunity to develop your skills in Snowflake, Azure, and DBT within a collaborative environment.
What you’ll do
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Assist in the design, development, and maintenance of data pipelines using Snowflake and supporting Azure services (e.g., Azure Data Factory, Azure Data Lake Storage).
•
Develop and maintain data transformation logic using DBT (data build tool) for data modeling and quality.
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Support the ingestion and integration of data from various sources into our Snowflake data platform.
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Monitor and troubleshoot data pipeline issues, ensuring data accuracy and availability.
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Leverage GenAI-assisted development tools to accelerate pipeline construction, code optimization, and documentation.
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Collaborate with senior engineers to implement best practices for data governance, security, and performance optimization.
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Contribute to the documentation of data models, pipelines, and processes.
•
Participate in code reviews and contribute to a culture of continuous improvement.
Qualifications
•
Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.
•
Experience with any programming language (e.g., Python, Scala).
•
Familiarity with foundational data concepts (e.g., ETL/ELT, data warehousing, data modeling).
•
Basic understanding of SQL and relational databases.
•
Exposure to cloud platforms (preferably Azure).
•
Eagerness to learn and develop skills in Snowflake, Azure, and DBT.
•
Strong problem-solving skills and attention to detail.
•
Excellent communication and collaboration skills.
•
Ability to work independently and as part of a team.
Bonus Points (Nice to Have)
•
Prior experience or hands-on projects utilizing Snowflake (experience with alternative cloud data platforms is acceptable, but Snowflake is preferred).
•
Hands-on experience with GenAI coding tools and agents (e.g., Cursor, Claude Code, Cortex Code) to streamline development workflows.
•
Prior coursework or projects involving data engineering concepts.
•
Familiarity with version control systems (e.g., Git).
•
Understanding of data visualization tools (e.g., Power BI).
•
Certifications related to Azure, Snowflake, or data engineering.
Use of AI in our Hiring Process:
We are committed to a fair and transparent hiring process. As part of our recruitment practices, we may use artificial intelligence (AI)–based tools. Our tool is designed to assess role-related qualifications in a consistent way and is always used together with human review and decision-making. If you have any questions or concerns about the use of AI in our hiring process, or if you would prefer an alternative assessment method, please let us know and we will be happy to accommodate.
About the company
About PureFacts Financial Solutions
PureFacts is the leader in the Revenue Performance Management category for wealth and asset management firms. The PureRevenue™ Platform helps organizations maximize revenue potential by connecting pricing, billing, compensation, advisor behavior, and AI-powered intelligence within a single Revenue Book of Record. By transforming fragmented revenue processes into a coordinated growth system, firms gain greater visibility, stronger pricing discipline, improved revenue capture, and more effective advisor alignment. The result is faster organic growth, improved profitability, and increased enterprise value. For more than 25 years, PureFacts has helped leading financial institutions turn revenue from an operational process into a strategic advantage.
At PureFacts, we are building an AI-native platform and company. We embed AI, intelligent automation, and agentic workflows across our products and operations to detect anomalies, surface insights, streamline repetitive work, and support faster, better decision-making. In a highly regulated industry, we believe AI must be practical, governed, and auditable—amplifying human expertise while helping our teams and clients focus on higher-value, strategic work.
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