Senior Analytics Engineer – Data Modeling
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
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Original job description
Senior Analytics Engineer – Data Modeling (Databricks), Capital Markets
Duration: 12 Months (Possible extension)
Location: Toronto - Hybrid- 1 day onsite
Start Date: Oct 5th
Interview Process: Codility test- 2 rounds (final in person)
Senior Analytics Engineer – Data Modeling (Databricks), Capital Markets
About the Role
We're looking for a Senior Analytics Engineer to own data design and modeling for Capital Markets business domains. This role combines senior data engineering and data modeling:
You'll partner directly with business teams and deliver trusted, well-modeled data solutions on Databricks. The role is focused on modeling and business solutions rather than platform or pipeline infrastructure, and it works as a peer to the team's data engineers.
Key Responsibilities
Business Partnership & Ownership
- Act as the data design and modeling SME for an assigned business domain.
- Partner with business stakeholders to understand goals, gather requirements, and translate them into scalable data solutions.
- Own solution design end to end, from requirements to production, using reusable, cost-efficient patterns.
Data Design & Modeling
- Design conceptual, logical, and physical data models (dimensional, slowly changing, historical/as-of) across medallion layers.
- Build the transformations that implement these models, with data quality and validation built in.
- Define data standards, business definitions, and documentation for the domain's data products.
Data Products & Analytics Enablement
- Deliver curated, analysis-ready datasets and semantic layers for reporting, self-service analytics, and ML.
- Resolve complex data questions for business users, and turn recurring ad hoc requests into scalable solutions.
- Share knowledge and help raise modeling standards across the team.
Required Skills & Experience
- Degree in Computer Science, Engineering, Mathematics, Finance, or a related field
- 6+ years in data engineering, analytics engineering, data modeling, or BI, with a strong focus on data modeling
- 2+ years hands-on with Databricks (Delta Lake, Unity Catalog, Databricks SQL)
- Expert SQL and strong dimensional modeling skills (star schemas, SCDs)
- Proficient in Python/PySpark
- Proven experience working directly with business stakeholders to gather requirements and deliver solutions
Nice to Have
- Capital Markets or financial services experience (trades, positions, risk, P&L, reference data)
- Reporting and visualization (Power BI, Plotly, Databricks AI/BI Dashboards)
- Semantic layers and AI-powered BI (Unity Catalog Metric Views, Databricks Genie)
- Large-scale data migration experience
- Databricks Certified Data Engineer (Associate or Professional)
More about this job
Responsibilities
Own data design and modeling for an assigned Capital Markets domain, partnering with business stakeholders to translate requirements into scalable, production-ready solutions. Build and document modeled data products, transformations, and semantic layers that support reporting, self-service analytics, and machine learning.
Requirements
Requires a degree in Computer Science, Engineering, Mathematics, Finance, or a related field, plus at least six years of relevant experience focused on data modeling. Candidates need at least two years of hands-on Databricks experience, expert SQL and dimensional modeling skills, Python/PySpark proficiency, and experience delivering solutions with business stakeholders.
Skills
- Databricks
- Data Modeling
- SQL
- Python
- PySpark
- Dimensional Modeling
- Delta Lake
- Unity Catalog
- Databricks SQL
- Data Engineering
- Data Quality
- Business Requirements Gathering
- Semantic Layers
- Capital Markets
- Slowly Changing Dimensions
- Data Migration
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
Keywords
- Databricks
- Delta Lake
- Unity Catalog
- Databricks SQL
- Databricks AI/BI Dashboards
- Databricks Genie
- Unity Catalog Metric Views
- SQL
- Python
- PySpark
- Data Modeling
- Dimensional Modeling
- Star Schemas
- Slowly Changing Dimensions
- Historical and As-Of Modeling
- Medallion Architecture
- Data Engineering
- Analytics Engineering
- Business Intelligence
- Data Quality
- Semantic Layers
- Self-Service Analytics
- Machine Learning
- Capital Markets
- Trades
- Positions
- Risk
- Profit and Loss
- Reference Data
- Power BI