Business Analyst (DataBricks/DataLake)

Jay Analytix•Toronto, ON

11d•Hybrid

About The Position

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.

Requirements

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 Haves

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

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