Senior Analytics Engineer (m/f/d)

autotradercanada; Toronto; On-site; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Gym discounts

Employee and Family Assistance program

Virtual wellness events

Conferences & training budget

Regular internal training programs

3% matching pension

Competitive salary

Annual bonus structure

Job summary

AutoTrader Canada is seeking a Senior Analytics Engineer to lead complex analytics initiatives, create scalable data products, and guide architectural choices. You will own end-to-end analytics projects, collaborate with cross-functional teams, and drive AI-driven capabilities across the data stack.

The role emphasizes strong SQL, Python, and cloud-native design, with a focus on data quality, governance, and reliable operational analytics.

Qualifications

• 7+ years of experience in Analytics Engineering, Data Engineering, or a related data role.
• Deep experience designing, building, and scaling analytical models and reusable data products.
• Advanced SQL skills and strong knowledge of dimensional and semantic modeling.
• Strong experience with cloud-native analytical platforms, ideally AWS services such as Glue, Athena, S3, or MWAA.
• Python experience for data processing, automation, validation, or troubleshooting.
• Proven track record of owning complex technical initiatives within a team.
• Experience setting technical direction, resolving ambiguity, and aligning stakeholders.
• Understanding of data quality, testing, observability, and governance in analytical systems.

Responsibilities

• Own complex analytics engineering workstreams from problem framing through delivery and adoption.
• Design and evolve scalable analytical models, semantic layers, and reusable data products.
• Set technical direction for team-owned models and analytical systems.
• Resolve ambiguity and align stakeholders around clear, pragmatic technical decisions.
• Improve modeling standards, documentation, testing, review practices, and quality gates.
• Drive consistency in KPIs, metrics, and analytical logic.
• Partner with Data Platform, Product Analytics, Engineering, and Data Governance teams.
• Improve performance, reliability, and cost efficiency of AWS-based workloads.
• Contribute to AI-driven capabilities such as text-to-SQL and semantic modeling.

Skills

Analytics Engineering

Data Modeling

SQL

Python

Stakeholder Alignment

Tools

AWS Glue

AWS Athena

Amazon S3

MWAA (Airflow)

Semantic Modeling Tools

Job description

We are a Canadian leader in digital automotive solutions. Our flagship brands - AutoTrader.ca , AutoSync , Dealertrack Canada and CMS - help Canadians buy, sell, and finance vehicles with confidence.

AutoTrader.ca is Canada's largest automotive marketplace, with over 25 million monthly visits .

As part of AutoScout24 group , Europe's largest online car marketplace, we're shaping the future of automotive retail in Canada and beyond.

As a Senior Analytics Engineer , you will be a senior technical contributor within the Analytics Engineering team and help shape the data foundations behind reporting, self-service analytics, and AI-driven decision-making. You will own complex technical workstreams, set direction for team-level analytical systems, and help improve the standards, practices, and architecture used across the team.

What youʼll do

• Own complex analytics engineering workstreams from problem framing through delivery and adoption
• Design and evolve scalable analytical models, semantic layers, and reusable data products
• Set technical direction for team-owned models and analytical systems
• Resolve ambiguity and align stakeholders around clear, pragmatic technical decisions
• Improve modeling standards, documentation, testing, review practices, and quality gates
• Drive consistency in KPIs, metrics, and analytical logic
• Partner with Data Platform, Product Analytics, Engineering, and Data Governance teams
• Improve the performance, reliability, and cost efficiency of AWS-based analytical workloads
• Contribute to AI-driven capabilities such as text-to-SQL, semantic modeling for AI, automated insights, and conversational analytics
• Guide complex refactoring, migrations, and technical debt reduction
• Review analytical solutions for correctness, maintainability, privacy, security, performance, and business fit
• Mentor analytics engineers and analysts through reviews, pairing, and technical guidance
• Turn recurring quality or delivery issues into reusable standards, automation, and documentation
• Connect technical decisions to product, operational, and business outcomes

You come with

• 7+ years of experience in Analytics Engineering, Data Engineering, or a related data role
• Deep experience designing, building, and scaling analytical models and reusable data products
• Advanced SQL skills and strong knowledge of dimensional and semantic modeling
• Strong experience with cloud-native analytical platforms, ideally AWS services such as Glue, Athena, S3, or MWAA
• Practical Python experience for data processing, automation, validation, or troubleshooting
• A strong track record of owning complex technical initiatives within a team or across closely related teams
• Experience setting technical direction, resolving ambiguity, and aligning stakeholders
• Strong understanding of data quality, testing, observability, documentation, and operational ownership
• Experience improving modeling standards, development workflows, review practices, or quality gates
• The ability to influence technical and business stakeholders through clear reasoning and communication
• Experience mentoring analytics engineers, analysts, or other data practitioners
• A good understanding of data privacy, security, governance, and compliance in analytical systems
• Experience with semantic layers, shared metric frameworks, or AI-driven analytics is a strong advantage
• A proactive, collaborative, and solution-driven mindset

What success looks like

• You act as a trusted senior technical contributor within the team
• You own complex workstreams and help the team navigate difficult technical decisions
• Core models and semantic assets become more scalable, reliable, and reusable
• Engineering quality improves through stronger standards, reviews, mentoring, and automation
• Stakeholders trust your technical judgment and involve you early in important decisions
• You improve not only individual data products, but also the systems and practices around them

What's in it for you:

• Gym discounts
• Employee and Family Assistance program
• Virtual wellness events
• Conferences & training budget
• Regular internal training programs
• Financial planning with 3% matching Pension
• Competitive salary
• Annual bonus structure

Compensation

Our ranges reflect the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role the total rewards package m

Compensation

Our ranges reflect the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role the total rewards package m