Summary
✨ AI‑Generated
A Senior Analytics Engineer is sought to own data design and modeling for capital-markets business domains. The role combines senior data engineering with business-oriented data modeling, partnering directly with business stakeholders to deliver trusted, well-modeled solutions on Databricks. Candidates should have 6+ years of experience in data engineering, analytics, or data modeling, including 2+ years with Databricks, along with expert SQL and strong Python/PySpark skills.
Highlights
12-month senior role with possible extension, combining data engineering and business-focused data modeling. Offers direct partnership with business teams and ownership of trusted data solutions on Databricks.
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)
Role Highlights: Must-have profile
6+ years data engineering/analytics/data modeling + 2+ years Databricks + expert SQL + strong data modeling + Python/PySpark.
Ideal candidate: Senior Data Engineer / Analytics Engineer who has strong Databricks + SQL + data modeling experience, preferably from Capital Markets or banking.
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 field6+ years in data engineering, analytics engineering, data modeling, or BI, with a strong focus on data modeling2+ years hands-on with Databricks (Delta Lake, Unity Catalog, Databricks SQL)Expert SQL and strong dimensional modeling skills (star schemas, SCDs)Proficient in Python/PySparkProven 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 experienceDatabricks Certified Data Engineer (Associate or Professional)
