Senior Engineer, Data & Analytics at Kinaxis
Remote, British Columbia, Canada -
Full Time


Start Date

Immediate

Expiry Date

09 Oct, 25

Salary

0.0

Posted On

09 Jul, 25

Experience

6 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

ABOUT KINAXIS

Elevate your career journey by embracing a new challenge with Kinaxis. We are experts in tech, but it’s really our people who give us passion to always seek ways to do things better. As such, we’re serious about your career growth and professional development, because People matter at Kinaxis.
In 1984, we started out as a team of three engineers. Today, we have grown to become a global organization with over 2000 employees around the world, with a brand-new HQ based in Kanata North in Ottawa. As one of Canada’s Top Employers, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.
At Kinaxis, we power the world’s supply chains to help preserve the planet’s resources and enrich the human experience. As a global leader in end-to-end supply chain management, we enable supply chain excellence for all industries, with more than 40,000 users in over 100 countries. We are expanding our team as we continue to innovate and revolutionize how we support our customers.

ABOUT THE TEAM

The Data & Analytics team drives Kinaxis’ transformation into a data-driven organization. By designing and governing scalable, modern data ecosystems, we ensure reliable, high-quality, and accessible data that empowers decision-making across the company. Our expertise spans data integration, engineering, governance, business intelligence, and cloud cost optimization, enabling actionable insights, operational efficiency, and new business opportunities.
We are seeking a Senior Engineer, Data and Analytics to help advance Kinaxis’ data ecosystem. This role focuses on data integration, engineering, modeling, and business intelligence, with an emphasis on transforming legacy systems into a cloud-native stack using Databricks, dbt, and other cloud platforms.

GOOD TO HAVE:

  • Experience working in SaaS environments or product-oriented data teams.
  • Certifications such as dbt Analytics Engineer, Google Cloud Professional Data Engineer, or Looker Certified Developer.
    Work With Impact: Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day—when we see store shelves stocked, when medications are available for our loved ones, and so much more.
    Work with Fortune 500 Brands: Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Lockheed Martin, Yamaha, P&G, Honda, and more.
    Social Responsibility at Kinaxis: Our Diversity, Equity, and Inclusion Committee weighs in on hiring practices, talent assessment training materials, and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to net-zero operations strategy for the long term. We are involved in our communities and support causes where we can make the most impact.

People matter at Kinaxis and these are some of the perks and benefits we created for our team:

  • Flexible vacation and Kinaxis Days (company-wide day off on the last Friday of every month)
  • Flexible work options
  • Physical and mental well-being programs
  • Regularly scheduled virtual fitness classes
  • Mentorship programs and training and career development
  • Recognition programs and referral rewards
  • Hackathons

Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates, including those with specific needs or disabilities. If you require an accommodation, please reach out to us at recruitmentprograms@kinaxis.com. Please note that this contact information is strictly for accessibility requests and cannot be used to inquire about application statuses.
Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description, to identify candidates whose education, experience and skills most closely match the requirements of the role. After the initial screening, all subsequent decisions regarding your application, including final selection, are made by our human recruitment team. AI does not make any final hiring decisions.

Responsibilities

WHAT YOU WILL DO

You will play a key role in developing and maintaining scalable, performance-optimized BI solutions and data pipelines, enabling self-service analytics and driving actionable insights across the organization. Your work will ensure the quality and reliability of data that supports decision-making and drives new business opportunities.
Finally, your ability to engage stakeholders and craft compelling data stories will be critical to your success in this role.

KEY RESPONSIBILITIES:

  • Lead the design and delivery of end-to-end BI solutions, from raw data ingestion to curated reporting assets, ensuring scalability, performance, and reusability.
  • Define and implement semantic model strategies across both the backend (dbt-based data marts) and frontend (Power BI datasets, LookML models) to support governed, reusable metrics and dimensions.
  • Build and maintain modular dbt pipelines on modern cloud data platforms such as BigQuery or Databricks, delivering consumption-ready datasets aligned with business needs.
  • Develop semantic models and dashboards in Power BI or Looker, optimizing for performance, usability, and alignment with business logic.
  • Own BI platform governance, including workspace organization, content lifecycle, user access management, and platform administration.
  • Make informed architectural decisions on where transformation logic should reside—in the data warehouse vs BI layer—based on maintainability and performance trade-offs.
  • Define and enforce best practices for data modeling, version control (Git), testing, and CI/CD across analytics workflows.
  • Collaborate with business stakeholders and product owners to translate requirements into well-structured, insightful data products and visual narratives.
  • Mentor engineers and analysts, helping elevate the team’s BI architecture, semantic modeling, and platform maturity.
  • Continuously evaluate and improve BI tooling, modeling approaches, and cloud data platform capabilities in line with industry trends and business needs.
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