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Data Dimensions Jobs in Ontario (NOW HIRING)

25-053 Data Architect

Pickering, ON · On-site +1

$85 - $100/hr

... dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact ... Azure Data Factory, Azure Data Lake, Azure SQL Databases, Azure Data Warehouse, Azure Synapse ...

Data Engineer

Toronto, ON · Hybrid

CA$90K - CA$125K/yr

  • Medical

  • Retirement

Strong understanding of data modeling concepts including medallion architecture, data vault, grain, fact tables, dimensions, and schema design. * Hands-on experience building and maintaining ...

Data Engineer

Toronto, ON · Hybrid

CA$90K - CA$125K/yr

  • Medical

  • Retirement

Strong understanding of data modeling concepts including medallion architecture, data vault, grain, fact tables, dimensions, and schema design. * Hands-on experience building and maintaining ...

Design canonical domain models, defining core entities, relationships, facts, dimensions, and ... Design for multiple external data feeds in varying formats, without assuming control over upstream ...

Clinical Data Scientist

Unionville, ON · On-site

CA$108K - CA$157K/yr

Develop and apply structured data assessment frameworks to evaluate data quality dimensions, including accuracy, completeness, validity, timeliness, longitudinally consistency, and integrity * Assess ...

Clinical Data Scientist

Toronto, ON · On-site

CA$108K - CA$157K/yr

Develop and apply structured data assessment frameworks to evaluate data quality dimensions, including accuracy, completeness, validity, timeliness, longitudinally consistency, and integrity * Assess ...

Clinical Data Scientist

Mississauga, ON · On-site

CA$108K - CA$157K/yr

Develop and apply structured data assessment frameworks to evaluate data quality dimensions, including accuracy, completeness, validity, timeliness, longitudinally consistency, and integrity * Assess ...

Develop and apply structured data assessment frameworks to evaluate data quality dimensions, including accuracy, completeness, validity, timeliness, longitudinally consistency, and integrity * Assess ...

Clinical Data Scientist

Maple, ON · On-site

CA$108K - CA$157K/yr

Develop and apply structured data assessment frameworks to evaluate data quality dimensions, including accuracy, completeness, validity, timeliness, longitudinally consistency, and integrity * Assess ...

Demonstrated understanding of dimensional modeling concepts, including Star Schema, facts, dimensions, and KPI design for analytics use cases. * Proven experience implementing data governance ...

... dimensions, and lineage - Supporting surrounding teams in getting value out of the platform's data through regular reporting and analysis 90 days: - Owning and automating reporting workflows from ...

Senior Data Engineer

Mississauga, ON · On-site

CA$130K - CA$140K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Strong foundational knowledge of Data Warehousing and Lakehouse architectures, including star/snowflake schemas, Slowly Changing Dimensions (SCD), and data governance frameworks to ensure high ...

Full Stack Data Science Engineer

Toronto, ON · On-site

CA$120K - CA$154K/yr

Lead end-to-end performance diagnostics across customer, product, and advisor dimensions to identify growth, efficiency, and primacy opportunities. * Translate curated data into actionable insights ...

Functional Engineer

Toronto, ON

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Integration & Data Management: Design, enhance, and validate integrations between UKG Dimensions and connected platforms including SAP SuccessFactors, payroll systems, ServiceNow, data platforms, and ...

Build data pipelines aligned with Data Warehousing concepts, including fact/dimension loads, incremental processing, and Slowly Changing Dimensions (SCD) * Manage Talend jobs using Talend Management ...

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Data Dimensions information

What are data dimensions?

Data dimensions are attributes or perspectives by which data can be categorized, organized, and analyzed. In the context of data management and analytics, dimensions such as time, geography, product, or customer allow users to slice and dice data for deeper insights. For example, a sales dataset might have dimensions like region and sales period, enabling users to analyze performance by different locations or times. Understanding data dimensions is essential for building effective reports, dashboards, and business intelligence solutions. They help transform raw data into meaningful information for decision-making.

What are the key skills and qualifications needed to thrive as a data analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in mathematics or computer science. Familiarity with data analysis tools like SQL, Excel, Python, R, and data visualization platforms such as Tableau is typically required. Excellent problem-solving, attention to detail, and effective communication skills set top performers apart in this role. These skills are essential for extracting meaningful insights from data, supporting business decisions, and clearly conveying findings to stakeholders.

What are some common challenges faced by professionals working in data dimensions roles, and how can they overcome them?

Professionals in data dimensions roles often encounter challenges related to ensuring data quality, consistency, and proper integration across multiple data sources. Managing large volumes of data and maintaining accurate dimensional hierarchies can be complex, especially in organizations with rapidly evolving datasets. To overcome these challenges, it's important to establish clear data governance practices, collaborate closely with data engineers and business analysts, and leverage robust data management tools. Continuous learning and staying updated on best practices in data modeling and warehousing also contribute to long-term success in this field.

What are popular job titles related to Data Dimensions jobs in Ontario?

For Data Dimensions jobs in Ontario, the most frequently searched job titles are:

Infographic showing various Data Dimensions job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

25-053 Data Architect

Morson Talent

Pickering, ON • On-site, Remote

$85 - $100/hr

Full-time

Re-posted 14 days ago


Job description

Job Description 25-053 Data Architect Resume Due Date: Monday, April 14, 2025 (5:00PM EST) Number of Vacancies: 1 Level: MP6 Hourly Rate: $85 - $100/hour Duration: 12 Months Hours of work: 35 Location: 889 Brock Road, Pickering (Hybrid - 4 days remote) Job Overview JOB FUNCTION As a Data Architect you will be responsible for leading the Azure architecture. design and delivery of data models and data products which enable innovative, customer-centric digital experiences. You will be working as part of a cross-discipline agile team who helps each other solve problems across all business areas.

You will be a thought leader and subject matter expert on data lake & data warehousing and modeling activities for the team and use your influence to ensure that the team produces best-in class data solutions that leverage repeatable, maintainable, and well-documented design patterns. You will employ best practice in development, security, accessibility and design to achieve the highest quality of service for our customers. JOB DUTIES Lead the architecture.

design and oversee implementation of modular and scalable data ELT/ETL pipelines and data infrastructure on Azure and Databricks leveraging the wide range of data sources across the organization Design curated common data models that offer an integrated, business-centric single source of truth for business intelligence, reporting, and downstream system use Work closely with infrastructure and cyber teams to ensure data is secure in transit and at rest Create, guide and enforce code templates for delivery of data pipelines and transformations for structured, semi-structured and unstructured data sets Develop modeling guidelines that ensure model extensibility and reuse by employing industry standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact optimizations Establish standards database system fields, including primary and natural key combinations that optimize join performance in a multi-domain. multiple subject area physical (structured zone) and semantic model (curated zone) Ensure model extensibility by employing industry standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact optimizations Transform data and map to more valuable and understandable semantic layer sets for consumption, transitioning from system centric language to business-centric language Collaborate with business analysts, data scientists, data engineers, data analysts and solution architects to develop data pipelines to feed our data marketplace Introduce new technologies to the environment through research and POCs. and prepare POC code designs that can be implemented and productionized by developers Work with tools in the Microsoft Stack; Azure Data Factory, Azure Data Lake, Azure SQL Databases, Azure Data Warehouse, Azure Synapse Analytics Services, Azure Databricks, Microsoft Purview, and Power Bl Work within the agile SCRUM work management framework in delivery of products and services, including contributing to feature & user story backlog item development, and utilizing related Kanban/SCRUM toolsets Document as-built architecture and designs within the product description Design data solutions that enable batch, near-real-time, event-driven, and/or streaming approaches depending on business requirements Design & advise on orchestration of data pipeline execution to ensure data products meet customer latency expectations, dependencies are managed, and datasets are as up-to-date as possible, with minimal disruption to end-customer use Ensure that designs are implemented with proper attention to data security, access management.

and data cataloging requirements Approve pull requests related to production deployments Demonstrate solutions to business customers to ensure customer acceptance and solicit feedback to drive iterative improvements Assist in troubleshooting issues for datasets produced by the team (Tier 3 support), on an as-required basis Guide data modelers, business analysts and data scientists in the build of models optimized for KPI delivery, actionable feedback/writeback to operational systems and enhancing the predictability of machine learning models and experiments Develop Bicep or Terraform templates to manage Azure Infra as code Perform hands on data engineering work to build data ingestion and data transformation pipelines Qualifications EDUCATION Requires an extensive knowledge in designing a data model to solve a business problem, specifying a data pipeline design pattern to bring data into a data warehouse, optimizing data structures to achieve required performance, designing low-latency and/or event-driven patterns of data processing, creation of a common data model to support current and future business needs. This knowledge is considered to be normally acquired through the completion of a four year University education in computer science. computer/software engineering or other relevant programs within data engineering, data analysis, artificial intelligence, or machine learning.

EXPERIENCE Experience guiding data lake ingestion and data modeling projects in the Azure cloud environment; experience in modeling relational and in-memory models with star/snowflake schemas; experience with designing and implementing event-driven (pub/sub), near-real-time, or streaming data solutions, involving structured, semi-structured and unstructured data across various platforms and. A period of over 6 years and up to and including 8 years in data modeling, data warehouse design, and data solution architecture in a Big Data environment is considered necessary to gain this experience.