1

Analytic Engineer Jobs in Toronto, ON (NOW HIRING)

Analytics Engineer, Enterprise Data

Toronto, ON · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Analytics Engineer, Enterprise Data See It. Build It. Own it. Sangoma is a global leader in business communications, delivering cloud-based solutions that help organizations connect, collaborate, and ...

Analytics Engineer, Enterprise Data

Toronto, ON · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Analytics Engineer, Enterprise Data See It. Build It. Own it. Sangoma is a global leader in business communications, delivering cloud-based solutions that help organizations connect, collaborate, and ...

Senior Analytics Engineer

Toronto, ON · On-site

CA$100K - CA$150K/yr

Executive KPIs, conversion funnels, cohort analytics, and marketing attribution across Google Ads ... Enjoy ambiguous business-logic modeling: reverse-engineering a production schema, interviewing ...

The Data Engineer works closely with analytics, operations, IT, data governance, and AI & Automation stakeholders to move data initiatives from design through production, while maintaining data ...

Senior Manager - Data Engineering

Toronto, ON · On-site +1

CA$120K - CA$160K/yr

Lead the build-out of Canada's Gold/semantic consumption layer with data contracts and SLAs, and retire the legacy analytics warehouse. * Partner with the Lead Data Engineer on system design of our ...

Pavement Engineer

Markham, ON · Hybrid

CA$74K - CA$123K/yr

Conducting pavement data processing and analysis and pavement designs for new construction ... Conducting geotechnical engineering assessments and analyses for a range of project types

You'll play a key role in shaping technical direction, mentoring engineers, establishing engineering best practices, and delivering scalable data products that enable analytics, AI, and machine ...

... engineering best practices. * Applies iterative development practices across all phases of data ... Supports structured analysis and issue resolution by enabling accessible, well designed data assets ...

Partner with Professional Services to extract, transform, and analyze client data to optimize ... Collaborate with Product, Engineering, and Customer Success to deliver high-quality, actionable ...

Showing results 21-40

Analytic Engineer information

What is the difference between Analytic Engineer vs Data Engineer?

AspectAnalytic EngineerData Engineer
CredentialsTypically requires a degree in data science, statistics, or related fields; often certifications in SQL, Python, or cloud platformsRequires a degree in computer science, software engineering, or related fields; certifications in cloud services, SQL, and data pipeline tools
Work EnvironmentFocuses on analyzing data, building data models, and creating dashboards; collaborates with data scientists and business teamsBuilds and maintains data pipelines, databases, and infrastructure; works closely with data engineers and software developers
Industry UsageCommonly found in analytics teams, business intelligence, and data-driven decision-making rolesPrimarily in data infrastructure, big data projects, and data platform development

In summary, Analytic Engineers focus on transforming data into insights through analysis and modeling, while Data Engineers build the infrastructure to support data collection and storage. Both roles are essential in data teams but serve different functions within the data ecosystem.

Are analytic engineers in demand?

Analytic engineers are in high demand due to the increasing reliance on data-driven decision making across industries. They typically require skills in data modeling, SQL, and tools like Python or Spark, and often find opportunities in technology, finance, and healthcare sectors.

What does an analytic engineer do?

An analytic engineer designs, develops, and maintains data pipelines and systems to collect, process, and analyze large datasets. They often work with tools like SQL, Python, and cloud platforms to ensure data quality and accessibility for business insights and decision-making.

What are popular job titles related to Analytic Engineer jobs in Toronto, ON?

For Analytic Engineer jobs in Toronto, ON, the most frequently searched job titles are:

Infographic showing various Analytic Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 72% Full Time, 14% Part Time, and 14% Temporary. Highlights an 86% In-person, and 14% Hybrid job distribution.

Sr. Manager, Data Engineering & Analytics

Serve Robotics

Toronto, ON • Remote

$211K - $246K/yr

Full-time

Re-posted 29 days ago


Job description

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

Responsibilities

  • Lead the Team: Lead, mentor, and grow a team of data and analytics engineers. This includes hiring, performance management, career development, planning, and setting technical standards.

  • Technical Leadership: Define the data engineering and analytics roadmap, aligned with company goals. This includes prioritizing data platform investments, reporting needs, analytics capabilities, and cross-functional data initiatives.

  • Data Platform Ownership: Oversee the design, reliability, scalability, and governance of the company’s data infrastructure, such as data warehouses, data lakes, ETL/ELT pipelines, orchestration systems, semantic layers, and BI tooling.

  • Analytics Delivery: Ensure business stakeholders have accurate dashboards, metrics, reporting, and ad hoc analysis to support decision-making across functions such as product, operations, finance, sales, marketing, and executive leadership.

  • Empowering Self-Service: Make self-service an organization-wide goal by building rich, trusted datasets and enabling access through AI-powered natural language interfaces.

  • Data Quality and Governance: Establish standards for data accuracy, lineage, documentation, access controls, privacy, security, and compliance.

Qualifications

  • 6+ years of professional experience in data engineering and analytics including 2+ years experience leading teams of Sr. Data/Analytics Engineers.

  • Data leadership experience: Proven experience managing data engineering, analytics engineering, BI, or analytics teams, including hiring, coaching, performance management, and roadmap planning.

  • Strong technical foundation: Deep understanding of data warehouses, data lakes, ETL/ELT pipelines, orchestration, data modeling, BI platforms, semantic layers, and data quality practices.

  • Experience with modern data stacks: Hands-on experience with tools such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Fivetran, Looker, Tableau, Power BI, or similar platforms.

  • Cross-functional, business-oriented partnership: Strong track record partnering with executives and teams across product, operations, finance, engineering, sales and marketing, translating business goals into data strategy, dashboards and analytics products that improve decision-making.

  • AI-powered self-service analytics experience: Demonstrated ability to build trusted, governed data products and enable organization-wide access through natural language or AI-powered analytics interfaces, with strong controls for accuracy, security, privacy, compliance and usability.

  • Data governance expertise: Experience establishing standards for data quality, documentation, access controls, privacy, security, auditability, metric definitions, and trusted data products, including SOX, SOC2 compliance and compliance with international data policies and regulations (e.g., GDPR, data residency requirements).

  • Education or equivalent experience: Bachelor’s degree in computer science, data science, engineering, statistics, mathematics, information systems, or a related field. Advanced degrees are a plus.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada

  • Canada - ALL: $179,976 - CAD- $221,828 CAD

Compensation Range: $211K - $246K