PureFacts Financial Solutions Logo

PureFacts Financial Solutions

Lead Data Engineer

Reposted 29 Days Ago
Be an Early Applicant
In-Office
Toronto, ON, CAN
Senior level
In-Office
Toronto, ON, CAN
Senior level
Build, maintain, and optimize data pipelines and transformations on Snowflake and Azure. Develop DBT models, ingest diverse data sources, monitor pipelines, troubleshoot issues, collaborate on governance, and use GenAI-assisted tools to accelerate development and documentation.
The summary above was generated by AI

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.

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

  • 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.
  • Support the ingestion and integration of data from various sources into our Snowflake data platform.
  • Monitor and troubleshoot data pipeline issues, ensuring data accuracy and availability.
  • Leverage GenAI-assisted development tools to accelerate pipeline construction, code optimization, and documentation.
  • Collaborate with senior engineers to implement best practices for data governance, security, and performance optimization.
  • 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.

HQ

PureFacts Financial Solutions Toronto, Ontario, CAN Office

48 Yonge St, Toronto, ON M5E 1G6, Canada, Toronto, ON, Canada, M5E 1G6

Similar Jobs

27 Days Ago
In-Office
Toronto, ON, CAN
Senior level
Senior level
Healthtech
Leads and mentors data engineering teams while designing, deploying, and operating scalable data pipelines and platforms supporting analytics, AI/ML, and commercial use cases. Provides architectural leadership across cloud-native platforms, distributed processing, orchestration, data integration, and streaming architectures. Manages delivery priorities, stakeholder requirements, operational excellence, incident response, standards, and continuous improvement across enterprise data engineering initiatives.
Top Skills: AirflowAWSCi/CdDbtHadoopIicsInformaticaJavaKafkaPythonScalaSnowflakeSparkSQL
13 Days Ago
Hybrid
Toronto, ON, CAN
Senior level
Senior level
Artificial Intelligence • Healthtech • Professional Services • Analytics • Consulting
Lead design and build scalable data architectures, ETL pipelines, ingestion and data quality frameworks. Collaborate with cross-functional teams, enforce data governance, analyze data for insights, mentor junior engineers, and serve as the technical authority on data engineering best practices.
Top Skills: AWSAzureData Integration ToolsData LakeData ModelingData WarehouseETLGCPHadoopKafkaPythonSparkSQL
21 Days Ago
In-Office
Toronto, ON, CAN
Senior level
Senior level
Fintech
Design and build reusable, metadata-driven data and AI engineering frameworks using Databricks and cloud-native services. Architect and deploy Delta Live Tables, Lakeflow, and orchestrated Databricks workflows for automated data processing and AI agent deployment. Implement RAG/Graph RAG solutions and agent orchestration (AgentOps, Agent-bricks, LangGraph), integrate real-time streams, manage AI agent lifecycles, and ensure governance via Unity Catalog or AWS Glue.
Top Skills: Agent-BricksAgentic SystemsAgentopsAWSAws BedrockAws GlueAws SagemakerDatabricksDatabricks WorkflowsDelta Live TablesGraph RagLakeflowLakehouse ArchitectureLanggraphMcpMwaaRagStep FunctionsUnity Catalog

What you need to know about the Toronto Tech Scene

Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account