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

This role offers the opportunity to lead a data engineering function at the intersection of technology, analytics, and business strategy.

You will guide a team of data professionals while designing scalable data solutions that support marketing, customer engagement, and company growth.

The position combines hands-on technical leadership with cross-functional collaboration across data, engineering, and business teams.

You will transform complex datasets into reliable insights and actionable intelligence that influence strategic decisions.

Working in a remote environment, you will help shape modern data architecture, improve data quality, and drive innovation through advanced engineering practices.

This is a high-impact opportunity for a collaborative leader passionate about building strong data foundations and enabling data-driven success.

Accountabilities

In this leadership role, you will oversee the development of scalable data solutions while partnering closely with business teams to ensure data capabilities directly support organizational goals. You will lead technical initiatives, improve data reliability, and foster a culture of data-driven decision-making through strong collaboration and mentorship.

Lead and mentor a data engineering team, providing technical direction, guidance, and support in a fast-paced environment. Partner with marketing and business stakeholders to translate complex data needs into effective technical solutions and actionable insights. Promote data literacy by helping teams understand, interpret, and leverage data effectively. Design and maintain scalable data architectures, including data models, ETL/ELT pipelines, and centralized data warehouse solutions. Build and optimize integrations with key marketing and business platforms to improve data accessibility and performance. Establish and maintain data quality processes, including validation, monitoring, testing, and proactive issue resolution. Define and standardize business metrics to ensure consistent reporting and decision-making across teams. Shape the long-term data engineering roadmap and align technical priorities with strategic growth objectives. Stay current with emerging technologies and industry trends to continuously improve data capabilities.

Requirements

The ideal candidate brings strong data engineering expertise combined with business understanding and leadership experience. You are comfortable working hands-on with modern data technologies while guiding teams, managing complex projects, and collaborating with stakeholders across the organization.

Bachelor’s degree in Computer Science, Machine Learning, Engineering, or a related technical field. 8+ years of experience in data engineering, with at least 3 years working in fast-paced e-commerce or similar environments. Proven experience leading data initiatives, mentoring engineers, and driving cross-functional technical projects. Strong understanding of marketing data domains, including performance marketing, lifecycle marketing, and brand analytics. Experience implementing marketing measurement methodologies such as attribution models, incrementality testing, MMM, and conversion measurement frameworks. Advanced SQL and Python skills, with the ability to work deeply within modern data technology stacks. Extensive experience designing data architectures, building scalable pipelines, and developing data models for enterprise data platforms. Hands-on experience with cloud-based data environments and warehouse technologies. Strong understanding of data quality, governance, observability, and reliability practices. Ability to communicate technical concepts clearly to both technical and non-technical audiences. Proactive leadership style with strong problem-solving skills and a focus on delivering measurable business impact. Experience with Databricks or similar data platforms is considered an asset. Experience managing high-performing data teams and complex data integrations is preferred.

Benefits

Competitive compensation package with an estimated salary range of CAD $163,000-$185,000. Annual bonus program. Fully remote work flexibility. 100% employer-paid medical, dental, and vision coverage, with dependent coverage support. Life, accidental death and dismemberment, and disability insurance options. Company-matched RRSP contributions up to 4%. Comprehensive wellbeing programs supporting mental, physical, and emotional health. Lifestyle Spending Account for wellness and learning activities. Work-from-home stipend for eligible roles. Flexible time off policy, plus a dedicated company-wide break period between Christmas and New Year. Fully paid parental leave of 16 weeks for birthing and non-birthing parents. Family-building and fertility support services. Annual product gift card benefit. Opportunities to work with modern data technologies and contribute to impactful, data-driven initiatives.

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.

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.