2

Part Time Data Analytics Engineer Jobs in Toronto, ON

You will collaborate with engineering and business peers to design data environments that enable analytics, automation, and AI-driven insight. Key Responsibilities * Architect Microsoft Fabric ...

As a Data Quality Analyst, you will play a pivotal role in leveraging data to ensure the integrity ... This is a remote, part-time role (15-30 hours/week). Responsibilities & Scope: * Conduct ...

Business Analyst

Toronto, ON · Hybrid

CA$85K - CA$105K/yr

Bachelor's degree in Business Analytics, Finance, Data Analytics, Business Administration ... We offer a 40% child care discount to ALL Full-time employees & 10% to Part-time employees so that ...

... Analysts, Salesforce Admins, Developers, Architects, Marketing, Partnerships, Membership, Fan Experience, and Data teams to deliver scalable loyalty capabilities that deepen fan engagement across ...

AI Engineer Intern/Co-op

Markham, ON · Hybrid

CA$24 - CA$28/hr

... Data Science, or a related field. * Preferred candidates will have completed at least 2 years of ... This role is designed to support academic schedules with flexible part-time hours during academic ...

... part-time opportunities at any given time. We aim to provide our people with more than just a job ... Analyze client requirements, facility data, asset profiles, and service specifications to create ...

next page

Showing results 1-20

Part Time Data Analytics Engineer information

What are the key skills and qualifications needed to thrive as a Part Time Data Analytics Engineer, and why are they important?

To thrive as a Part Time Data Analytics Engineer, you need strong analytical skills, proficiency in statistics, and experience with data modeling, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with tools such as SQL, Python or R, and data visualization platforms like Tableau or Power BI is essential, with certifications in these tools considered advantageous. Excellent problem-solving abilities, attention to detail, and effective communication skills are important soft skills for this role. These skills ensure accurate data analysis, actionable insights, and efficient collaboration, which are critical for delivering value in a part-time capacity.

What does a Part Time Data Analytics Engineer do?

A Part Time Data Analytics Engineer is responsible for collecting, processing, and analyzing data to help organizations make informed decisions. They build and manage data pipelines, use programming languages like Python or SQL, and create dashboards or reports to visualize data trends. Working part time, they may focus on specific projects or support ongoing analytics needs, often collaborating with other team members to ensure data quality and actionable insights.

How does working as a part-time Data Analytics Engineer differ from a full-time position in terms of team collaboration and project ownership?

As a part-time Data Analytics Engineer, you'll often collaborate closely with full-time team members, focusing on specific tasks or projects that align with your available hours. You may be assigned to support data pipeline development, create dashboards, or perform data cleaning, but typically with a narrower project scope compared to full-time engineers. Communication and documentation are especially important, as you'll need to ensure smooth handoffs and updates for work that continues outside your scheduled hours. This structure provides flexibility but also requires proactive coordination to stay aligned with team goals and deadlines.
What are the most commonly searched types of Data Analytics Engineer jobs in Toronto, ON? The most popular types of Data Analytics Engineer jobs in Toronto, ON are:
What are popular job titles related to Part Time Data Analytics Engineer jobs in Toronto, ON? For Part Time Data Analytics Engineer jobs in Toronto, ON, the most frequently searched job titles are:
Infographic showing various Part Time Data Analytics Engineer job openings in Toronto, ON as of July 2026, with employment types broken down into 100% Part Time. Highlights an 50% In-person, and 50% Remote job distribution.
Part Time - Data Architect

Part Time - Data Architect

Architech

Toronto, ON

Part-time

Posted 15 days ago


Job description

Join Us in Building the Future
At Architech, we don’t just ship software. We partner with North America’s leading brands to modernize legacy platforms, embed AI into real operations, and launch digital products that transform business outcomes. Our engineers and designers harness cloud-native tools, autonomous agents, data-driven insights, and GenAI to drive measurable impact - replatforming systems in the cloud, optimizing customer journeys, or accelerating AI adoption across the enterprise. You’ll work at the intersection of strategy and execution, solving complex problems alongside smart, curious teammates across Canada and Poland. Backed by 20+ years of experience, a drive for excellence, and a culture rooted in growth and collaboration, this is where you thrive if you’re looking to deliver meaningful, high-stakes software solutions.
We’re Building a More Inclusive Tech Industry
We believe diversity leads to better outcomes. Nearly half of our team was born outside of Canada, and we speak 19+ languages. We’re 31% women, 57% BIPOC, and 14% LGBTQIA+. We’ve doubled the number of women in tech roles in the past year, and maintain a 0% gender pay gap across our delivery and technology teams. Inclusion here isn’t a buzzword, it’s backed by data, policy, and accountability.
How We Work Together
We’re a close-knit, collaborative group who care about doing excellent work, and doing it with integrity. Our values shape how we show up every day:
Think Big – Dream it, plan it, ship it
Be Open & Collaborate – Diverse minds build better solutions
Never Fail a Client – Own the outcome
Grow Our People – Feedback, learning, leadership
Do the Right Thing – Even when it’s hard
Embrace Change – Adapt fast, stay curious
Our people say it best: “Employees of different backgrounds interact well within our company” - and 97% agree. Another 96% say “Architech respects individuals and values their differences.”

Data Architect (Microsoft Azure / Microsoft Fabric / AWS/ Databricks)

Role Overview

The Data Architect (Azure Data Architect or Data Platform Architect) designs and leads the build-out of scalable, AI-ready data solutions using Microsoft Fabric, Azure, or AWS with Databricks data ecosystem. This role connects business goals to data architecture, ensuring platforms are secure, performant, and optimized for analytics and AI use cases.

You will define how data flows from raw ingestion (bronze) through transformation (silver) to curated, analytics-ready models (gold). You will collaborate with engineering and business peers to design data environments that enable analytics, automation, and AI-driven insight.

Key Responsibilities

  • Architect Microsoft Fabric environments: Design end-to-end data architectures, defining ingestion, transformation, and curation patterns that support analytics and AI workloads.
  • Lead Design and implement scalable data architectures on Databricks, including lakehouse solutions leveraging Delta Lake, Unity Catalog, and medallion architecture (bronze/silver/gold layers) to support enterprise analytics and ML workloads.
  • Lead Design and manage data lake architectures - Ensure efficient replication, synchronization, and data flow across Fabric workspaces and multi-zone environments.
  • Define business-aligned data models - Partner with stakeholders to understand reporting, analytics, and AI needs and design scalable, flexible data models.
  • Define data governance, security, and access control strategies — Use Unity Catalog and Microsoft Purview for centralized metadata management, fine-grained permissions, RBAC, encryption (at rest/in transit), data masking, and lineage tracking across workspaces.
  • AI readiness - Define structures, metadata, and access patterns that make data discoverable and usable for AI workloads such as retrieval-augmented generation (RAG), intelligent search, and summarization.
  • Familarity in implementing and managing Databricks Genie to enable self-service, natural language querying of enterprise data, empowering business users with AI-driven insights.
  • Framework alignment - Ensure all data architectures align with Microsoft's Cloud Adoption Framework (CAF) and the Azure/AWS Well-Architected Framework for consistency, scalability, and governance.
  • Performance and cost optimization - Guide architecture decisions related to Fabric SKUs, OneLake storage, and data refresh strategies for efficient scale and cost.
  • Collaboration and mentorship - Work closely with Data Engineers to translate architecture into delivery, promote data quality, and ensure design consistency.
  • Documentation and enablement - Produce reference architectures, blueprints, and reusable standards that accelerate future projects and maintain governance consistency.

Skills and Qualifications

  • 7+ years of experience in data architecture, data engineering, or data platform design, including:

At least 2 years working within the Microsoft Azure data ecosystem (Fabric, Synapse, ADF, Power BI).

At least 2 years of hands-on experience with Databricks (Delta Lake, Unity Catalog, lakehouse architecture).

  • Strong grasp of data lakehouse design principles, including ELT/ETL patterns, medallion architecture (bronze/silver/gold), and schema evolution.
  • Proficiency in SQL, with working knowledge of Python for automation, validation, and pipeline scripting.
  • Hands-on experience with data governance and metadata management tools, such as Microsoft Purview and/or Databricks Unity Catalog.
  • Practical understanding of data security fundamentals — RBAC, encryption (at rest/in transit), data masking, and privacy best practices.
  • Strong communication and cross-functional collaboration skills, with the ability to translate business needs into technical architecture and work across engineering, analytics, and business teams.
  • Strategic, iterative mindset — comfortable operating in AI-ready, fast-evolving, client-facing environments.

Tools and Technologies

Microsoft Fabric, Azure Data Factory, Synapse, Power BI, Azure SQL, Databricks, Data Lake Storage, Vector DB, Microsoft Purview, Python, SQL, Git, Terraform or Bicep, Azure Monitor.

Nice to Have

  • Experience applying architecture frameworks — Microsoft's Cloud Adoption Framework (CAF) and/or the Azure/AWS Well-Architected Framework to ensure scalability and governance consistency
  • Exposure to AI/semantic data enablement — metadata enrichment, retrieval-augmented generation (RAG), knowledge graph design, vector databases, and embedding pipelines.
  • Familiarity with modern data architecture paradigms — data product thinking, domain-driven design, or data mesh principles.
  • Familiarity with vector databases, semantic search, and embedding pipelines.
  • Familiarity with our data sources — exposure to platforms such as ChurnZero, Zendesk, Salesforce, Gong, and RocketLane is a plus.

Architech is an equal opportunity employer committed to diversity. Should you require any accommodations prior to or during the interview process, please indicate this during the interview process. We strongly encourage applications from racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities.