Business Analyst (DataBricks/DataLake)
Toronto Contract Mid-level Data Engineering
At a glance
Mid-level Data Engineering role at Jay Analytix. Toronto · contract.
Pay not stated Data Engineering salary
RoleData Engineering
SeniorityMid-level
LocationToronto
EmploymentContract
PostedJul 13, 2026 · 3mo ago
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Turn business and data needs into specifications, then track them through delivery
- Define source-to-target mappings, transformation rules and quality checks with engineering teams
- Profile source data and validate or reconcile records as they move to target platforms
- Coordinate user acceptance testing and document lineage, glossaries and metadata
- Run requirement workshops and maintain user stories, acceptance criteria and delivery backlogs
What you bring
- At least eight years as a business analyst, including substantial work on data-focused projects
- Practical Databricks experience with notebooks and Delta Lake, plus knowledge of Lakehouse architecture
- Strong grasp of data lakes and cloud platforms, with Azure preferred and AWS or GCP also considered
- SQL skills for profiling and validation, and experience producing mapping and transformation documents
- A bachelor's degree in business, computing, information systems or a related area
Who this fits
This role suits an experienced analyst who can work across business and technical teams on data platform delivery. It is based in Toronto and requires three onsite days each week.
From the employer
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
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