Job Title or Location

Data Engineer

spruceinfotech - 3 Jobs
Toronto, ON
Posted today
Job Details:
Full-time
Experienced

Company Description

Spruce InfoTech, a leading IT firm, offers innovative and cost-effective solutions to help clients manage and transform their businesses. Our services are designed to guide companies of all sizes, from small businesses to Fortune 500 organizations, in maximizing their IT investment while reducing technology costs. Our team of experts has extensive technical knowledge in enterprise solutions, which helps organizations transform these solutions into a strategic asset that can drive new revenue and improve business operations.

Website

http://www.spruceinfotech.com

Job Description

Data Engineer

6+ Months

Toronto location. Hybrid work culture in downtown office.

Note: There will be a coding test round

What is the opportunity?
Capital Markets Data AI and Research Technology (DART) team is looking to hire a Data Engineer to build, manage and deploy cutting edge Data solutions.
What will you do?
• Design, build, and optimize scalable data pipelines to support Research Digitization, Banking, Global Markets, and Data Monetization use cases
• Develop and operationalize data products across structured and unstructured sources, including alternative data
• Deploy, manage, and performance-tune large-scale Spark workloads on Databricks, ensuring reliability, scalability, and cost-efficiency
• Collaborate with data scientists, quant teams, and business stakeholders to enable data-driven decision-making
• Contribute to automation efforts via CI/CD pipelines, infrastructure-as-code, and reusable data frameworks
Must Have
• Strong experience with Python and Spark (PySpark)
• Hands-on with Databricks (Jobs, Workflows, Delta Lake, Unity Catalog)
• Proficient in SQL for complex data transformations and optimizations
• Proficient in CI/CD principles, version control and best practices for deploying workloads to production
• Solid understanding of distributed data processing and production-grade data workflows
Nice to Have
• Exposure to Machine Learning workflows and tools like MLFlow
• Exposure to Generative AI stack (LLMs, Agents, MCP Servers)
• Familiarity with Snowflake, Airflow, or similar orchestration and warehousing platforms

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