This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Manager, Analytics Engineering based in Canada.

This role sits at the core of a modern data organization, responsible for transforming complex, high-volume business data into trusted, scalable, and AI-ready insights. You will lead a team of senior analytics engineers while remaining hands-on in shaping the technical direction of a critical data platform. The environment is fast-paced, remote-first, and highly collaborative, with strong partnerships across Finance, Risk, Product, and Operations. You will play a central role in building the semantic layer and data models that define the company’s single source of truth. This foundation powers dashboards, advanced analytics, and emerging AI-driven capabilities across the business. The role blends technical leadership, product thinking, and people management in equal measure, with a strong emphasis on impact, quality, and scalability.

Accountabilities:

In this role, you will lead and develop a high-performing analytics engineering team while actively contributing to the design, development, and evolution of a modern data platform built on Snowflake and dbt.

Lead, mentor, and grow a team of Lead and Senior Analytics Engineers, fostering a high-trust, high-performance engineering culture

Stay hands-on with SQL and dbt, driving technical design, code reviews, and engineering best practices across the data stack

Define and execute the roadmap for your team’s domain within the analytics platform, balancing delivery speed, technical debt, and long-term scalability

Design and evolve scalable data models, marts, and a robust semantic layer that serves as the organization’s single source of truth

Partner with cross-functional stakeholders (Finance, Risk, Sales, Product, Operations) to translate business needs into reliable, scalable data products

Champion data quality, governance, observability, and documentation to ensure trust in all downstream reporting and analytics

Drive engineering excellence across dbt practices, including testing strategies, incremental models, performance tuning, and CI/CD workflows

Contribute to hiring, interviewing, and onboarding efforts to strengthen and scale the analytics engineering organization

Requirements:

The ideal candidate combines strong technical depth in analytics/data engineering with proven leadership experience and the ability to translate business problems into scalable data solutions.

7+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence, with strong SQL and data modeling expertise

2+ years of people management experience leading senior-level engineers in a data or analytics environment

Deep hands-on experience with dbt and Snowflake (or similar cloud data warehouse), including modeling, testing, and deployment practices

Proven experience building or operating a semantic layer or metrics framework used as a trusted source of truth across an organization

Strong background in dimensional modeling, data architecture, and building scalable analytics pipelines

Demonstrated ability to partner with senior business stakeholders and translate complex requirements into durable data solutions

Excellent communication skills, with the ability to explain technical concepts clearly to both technical and non-technical audiences

Strong coaching and leadership skills with a track record of developing high-performing engineering teams

Comfortable working in fast-paced, remote-first environments with high ownership and autonomy

Benefits:

Competitive annual salary: CA$170,000 – CA$200,000

Performance-based bonus of up to 12%

Comprehensive health, dental, and vision insurance coverage

RRSP matching and retirement savings support

Flexible time-off policy and generous paid holidays

Paid parental leave and family support programs

Wellness, home office, and professional development reimbursements

Remote-first work environment with optional in-person collaboration spaces

Volunteering days and charitable donation matching programs

Strong focus on work-life balance, flexibility, and long-term career growth.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Manager, Analytics Engineering

Job Description - Manager, Analytics Engineering

Accountabilities:

Requirements:

Benefits:

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