Business Analyst (DataBricks/DataLake)

Business Analyst - Databricks & Data Lake

Location: Toronto, ON (Hybrid - 3 days onsite per week)

Experience: Minimum 8+ years

Employment Type: Full-Time / Contract (as applicable)

About the Role

We are seeking an experienced Business Analyst with strong hands-on exposure to Databricks and modern Data Lake / Lakehouse platforms to join our Toronto-based team. In this role, you will act as the bridge between business stakeholders and data engineering teams - gathering requirements, defining data mappings and transformation logic, and driving the delivery of large-scale data platform and migration initiatives. The ideal candidate combines deep business analysis fundamentals with practical knowledge of cloud data ecosystems.

Key Responsibilities

• Elicit, document, and manage business and data requirements for data lake, lakehouse, and analytics initiatives, translating them into functional and technical specifications
• Work closely with data engineers, architects, and platform teams to define source-to-target mappings, data transformation rules, and data quality requirements
• Support the design and delivery of solutions on Databricks (Delta Lake, notebooks, workflows, Unity Catalog) and cloud data lake platforms (Azure Data Lake Storage, AWS S3, or GCP)
• Analyze and profile source system data to assess quality, completeness, and fitness for migration or integration
• Define and document data lineage, business glossaries, and metadata to support data governance initiatives
• Develop and execute test plans, including UAT coordination, data validation, and reconciliation between legacy and target platforms
• Create process flows, user stories, use cases, and acceptance criteria within Agile delivery frameworks
• Facilitate workshops and requirement sessions with business users, product owners, and technical teams
• Support prioritization and backlog management with product owners; track requirements through to delivery
• Produce clear documentation and communicate findings, risks, and recommendations to both technical and non-technical stakeholders

Required Qualifications

• 8+ years of experience as a Business Analyst, with significant time spent on data-focused projects (data platforms, data warehousing, migrations, analytics)
• Hands-on experience with Databricks - working with notebooks, Delta Lake tables, and understanding of Lakehouse architecture concepts
• Strong understanding of Data Lake concepts and cloud data platforms (Azure preferred; AWS or GCP also considered) - data ingestion, storage layers (raw/curated/consumption), and data pipelines
• Proficiency in SQL for data profiling, analysis, and validation; ability to read/interpret PySpark or Python code an asset
• Experience creating source-to-target mapping documents, data dictionaries, and transformation specifications
• Solid grasp of data governance, data quality, and metadata management practices
• Experience with Agile methodologies and tools (Jira, Confluence, Azure DevOps)
• Strong analytical, problem-solving, and critical-thinking skills with high attention to detail
• Excellent communication, facilitation, and stakeholder management skills across business and technical audiences
• Bachelor's degree in Business, Computer Science, Information Systems, or a related field

Nice to Have

• Experience in financial services, banking, or insurance data environments
• Familiarity with data modeling concepts (dimensional modeling, medallion architecture)
• Exposure to BI and analytics tools (Power BI, Tableau) and how they consume lakehouse data
• Knowledge of ETL/ELT tools (Azure Data Factory, Informatica, dbt)
• Understanding of data privacy and regulatory requirements (PIPEDA, GDPR) as they relate to enterprise data
• Certifications such as CBAP, PMI-PBA, Azure Data Fundamentals (DP-900), or Databricks Lakehouse Fundamentals

Why Join Us

• Contribute to high-visibility data modernization initiatives on a leading Lakehouse platform
• Hybrid work model based in downtown Toronto
• Collaborative environment working alongside data engineering, governance, and business teams
• Competitive compensation and benefits package