Senior Analytics Engineer – Data Modeling

Toronto, ON
Hybrid
Posted Oct 3, 2026
1 position

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Employment type: Contract
Experience level: Senior · 5+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week
Office presence: 1 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

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.

Job details

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)

What you’ll do

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.