Data Architect at Kinaxis

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.

Location

Ottawa and Toronto, Canada (Hybrid)

Other locations in Canada - Remote

About The Team

The Data Architect, as a seasoned professional with extensive experience, is responsible for designing and managing data architecture at Kinaxis, which includes defining how data is stored, accessed, processed, and managed.

The incumbent will be a leader in designing and implementing data solutions to drive and support our global business by enabling intelligent decision making. As a technical expert, they will collaborate with stakeholders to understand requirements, design data solutions that support organizational goals, and to develop a world class data environment.

What you will do

• Define the modern cloud-based data architecture (on Databricks Lakehouse and GCP/Azure) with cross-functional teams that enable consistency and scalability.
• Architect and operationalize Medallion (Bronze–Silver–Gold) data models ensuring governance, data quality, and reusability across analytical and ML workloads.
• Combine data engineering and architecture expertise to design, develop, and deploy modern data warehouse and Lakehouse solutions, driving initiatives in data preparation, integration, exploration, and modeling.
• Participate in Architecture Review Boards, interface with other Cloud Architects, and act as the technical liaison for the department.
• Design, develop, and deliver complete data solutions, combining strong engineering execution with architectural design, managing pipelines, models, and workflows from ingestion through presentation, ensuring performance and cost efficiency.
• Facilitate discovery workshops, articulate solution value, build roadmaps, and communicate architectural strategy and business impact through data storytelling.
• Establish best practices and consistency across various Data on Cloud solutions.
• Design and build highly reusable and scalable cloud-native data ecosystems
• Assist in the development of comprehensive and strategic business cases used at management and executive levels for funding and scoping decisions on data solutions
• Understand data technology trends and the practical application of existing, new, and emerging technologies to enable new and evolving business needs.
• Partner closely with leadership and business stakeholders as a trusted and influential evangelist to identify important questions, define key metrics, cultivate a data driven and AI-ready culture.
• Design and implement data security measures to protect sensitive information.
• Work collaboratively with Data and Cloud Governance specialists to align on rules, processes, and standards, implementing strong governance through Unity Catalog, metadata management, and lineage tracking, while maintaining clear documentation of data architecture, flows, and dependencies.
• Design the lifecycle management process to seamlessly handle Python package and API dependency version changes
  
  

Technologies we use

• Programming languages: SQL, Python, Powershell
• Orchestration/Data Integration: Airflow, Informatica, Dagster, dltHub and others
• Databases: Databricks, Snowflake, Google BigQuery, SQL Server, PostgreSQL
• CI/CD: Github Actions, Github
• Modelling: DBT
• Presentation: PowerBI, Looker
  
  

What we are looking for

• BS or BA in Computer Science, Software Engineering, or demonstrated equivalent experience.
• 10+ years of experience in data architecture and engineering within high-tech or SaaS environments, with proven ability to design and deliver enterprise-scale data solutions.
• Strong hands-on expertise in modern cloud data architecture and engineering, leveraging the Databricks Lakehouse Platform (Delta Lake, Unity Catalog, Delta Live Tables, Databricks SQL) and Google Cloud Platform (BigQuery, Dataflow, Dataproc, Pub/Sub, Composer) to build and optimize scalable, governed, and high-performance data pipelines and models.
• Proficient in modern data engineering practices, including Medallion design, CI/CD automation (GitHub, Cloud Build), metadata and lineage management, data modeling and governance, and both streaming and batch data processing.
• Familiarity with AI/ML and analytics enablement, ensuring data readiness for model training, feature engineering, and intelligent insights.
• Strong understanding of data governance, data quality, and compliance frameworks, with experience implementing standards through cataloging and lineage tools.
• Experience deploying and operating cloud infrastructure, with the ability to collaborate effectively with Cloud and Infrastructure Architects to align design, security, and performance requirements.
• Strong written, verbal, and interpersonal communication skills.
• Highly adaptable, agile, and resilient in managing multiple concurrent projects; proactively seeks feedback to ensure alignment and continuous improvement.
• Certifications such as Google Cloud Professional Data Engineer or Cloud Architect, Databricks Certified Data Engineer (Professional), dbt, Looker, Terraform, FinOps, or Cloud Security are good to have.
  
  

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 [email protected]. 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.