Business Analyst (DataBricks/DataLake)
Jay Analytix · Toronto, Ontario, Canada
IT Services and IT Consulting · 11-50 employees
About the role
Act as the bridge between business stakeholders and data engineering teams to gather requirements and define data transformation logic. Drive the delivery of large-scale data platform migrations and analytics initiatives using Databricks and cloud data lakes.
What they look for
Requirements
Requires over 8 years of experience as a Business Analyst with deep expertise in Databricks, SQL, and cloud data platforms. A bachelor's degree in a technical or business field and proficiency in Agile methodologies are required.
Benefits
Full description
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