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Added 5 mins ago
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Added 2 hours ago
Data Engineer
Infotek Consulting Inc.
Toronto, ON
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Senior Analytics Engineer – Capital Markets Data
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Infotek Consulting Inc.

Data Engineer

Toronto, ON, Canada

Job type: Contract
Apply by: Oct 30, 2026
Experience: At least 2 years of hands-on Databricks experience.
Posting language: English
Posted: Sep 30, 2026

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Applications open in a new tab.

Original job description

Senior Analytics Engineer – Capital Markets Data

Location: Toronto

Contract Term: September 16, 2026 – September 15, 2027

Work Arrangement: Hybrid – 1 day per week in office

Rate: $80–$90/hour

Role Overview

We are seeking an experienced Senior Analytics Engineer to join a Capital Markets data team and take ownership of the design, structure, and delivery of business-focused data solutions.

This position sits at the intersection of data engineering, analytics, and data architecture, with a strong emphasis on data modeling rather than infrastructure engineering or pipeline development.

The successful candidate will work closely with business stakeholders to understand complex data requirements and translate them into reliable, scalable, and analysis-ready data products within a Databricks environment.

This individual will work alongside data engineers and will be responsible for taking data solutions from initial requirements and modeling through implementation and production delivery.

Key Responsibilities

Business & Data Solution Ownership

Serve as a senior subject matter expert for data architecture and modeling within an assigned business area.
Work directly with stakeholders to understand business processes, reporting needs, and analytical requirements.
Translate business requirements into practical and scalable data solutions.
Lead solution design from initial discovery through implementation and production deployment.
Develop reusable approaches that balance performance, maintainability, scalability, and cost.

Data Modeling & Transformation

Develop and maintain conceptual, logical, and physical data models.
Apply dimensional modeling techniques, including star schemas, slowly changing dimensions, and historical/as-of modeling.
Design data structures across appropriate layers within a medallion architecture.
Build SQL and PySpark transformations required to implement data models.
Incorporate data validation and quality controls into transformation processes.
Establish consistent business definitions, data standards, and documentation for data products.
Help identify and address data inconsistencies, gaps, and modeling challenges.

Analytics & Data Products

Create curated, trusted datasets that are ready for reporting, analytics, self-service consumption, and machine learning use cases.
Develop or contribute to semantic data layers that simplify access to complex business information.
Work with business users to investigate and resolve complex data-related questions.
Identify opportunities to replace recurring manual or ad hoc data requests with sustainable data solutions.
Promote consistent modeling practices and contribute to improving data standards across the broader team.
Share technical knowledge and mentor other team members where appropriate.

Required Qualifications

Bachelor's degree or equivalent education in Computer Science, Engineering, Mathematics, Finance, or a related discipline.
6+ years of experience across data engineering, analytics engineering, data modeling, business intelligence, or a related data discipline, with substantial hands-on data modeling experience.
At least 2 years of hands-on Databricks experience.
Strong knowledge of Delta Lake, Unity Catalog, and Databricks SQL.
Advanced/expert-level SQL skills.
Strong understanding of dimensional data modeling, including star schemas and slowly changing dimensions.
Proficiency with Python and PySpark.
Demonstrated ability to work directly with business stakeholders to gather requirements and translate them into technical data solutions.
Experience delivering data solutions through to production.

Preferred Qualifications

Previous experience working with Capital Markets or financial services data, including areas such as:
Trades
Positions
Risk
P&L
Reference data
Experience with business intelligence and visualization tools such as Power BI, Plotly, or Databricks AI/BI Dashboards.
Knowledge of semantic modeling and AI-enabled analytics, including Unity Catalog Metric Views or Databricks Genie.
Experience supporting large-scale data migration or modernization initiatives.
Databricks Data Engineer certification at the Associate or Professional level.

Ideal Candidate

The ideal candidate combines strong data modeling expertise with the ability to understand business problems and turn them into practical analytics solutions.

This role is particularly suited to someone who enjoys working directly with stakeholders, understands how business processes translate into data structures, and can operate comfortably between business requirements and hands-on technical implementation.

The successful candidate will bring strong SQL and Databricks capabilities, a solid understanding of modern data modeling practices, and the judgment to build data products that are both technically sound and genuinely useful to the business.

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More about this job

Responsibilities

Own the design and delivery of business-focused data solutions, translating stakeholder requirements into scalable data models and production-ready data products. Build and maintain modeled, validated datasets and semantic layers for reporting, analytics, self-service use, and machine learning.

Requirements

Requires a bachelor's degree or equivalent education and at least six years of relevant data experience, including substantial hands-on data modeling and at least two years using Databricks. Candidates need expert SQL skills, proficiency in Python and PySpark, knowledge of dimensional modeling and Databricks technologies, and experience translating business requirements into production data solutions.

Skills

Data Modeling
Databricks
Delta Lake
Unity Catalog
Databricks SQL
SQL
Python
PySpark
Dimensional Modeling
Star Schemas
Slowly Changing Dimensions
Data Architecture
Data Transformation
Data Quality
Stakeholder Requirements Gathering
Capital Markets Data

Visa sponsorship

Not detected in the job text

Keywords

Capital Markets
Financial Services
Data Engineering
Analytics Engineering
Data Architecture
Data Modeling
Dimensional Modeling
Star Schemas
Slowly Changing Dimensions
Historical Modeling
As-Of Modeling
Medallion Architecture
Databricks
Delta Lake
Unity Catalog
Databricks SQL
SQL
Python
PySpark
Data Validation
Data Quality
Semantic Modeling
Power BI
Plotly
Databricks AI/BI Dashboards
Unity Catalog Metric Views
Databricks Genie
Machine Learning
Data Migration

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