Data Analytics Specialist

Our Data Operations (In our Business Intelligence department) team sits between our business teams and the technical data team. We help turn business questions and sometimes messy data into structured, reliable information that people and AI tools can actually use.

You’ll help us build trusted data models, define clear metrics, improve data quality, and make our data easier to understand and use. You’ll also support how we use AI in analytics, helping ensure the information behind our AI tools is accurate, well-structured, and useful.

This role is for someone who enjoys solving problems and digging into why something is happening, not just reporting what happened. You don't need to be an AI expert. You do need a strong foundation in data and SQL, good judgment, and the curiosity to keep learning as our tools and ways of working evolve.

As a Particle (people of Article), you will have a high level of autonomy to solve challenging, meaningful problems the best way you can. That means you’re trusted to explore solutions you believe will work best (you’re the expert, after all). You’ll do all this while growing your skills within a company that is redefining the furniture industry.

Data Operations connects business questions with the data needed to answer them. You'll work closely with Business Operations, Data Engineering, and teams across Article, including Sales, Customer Service, Supply Chain Planning, and Logistics.

We are a hybrid team. You'll be in our Vancouver office 3 days per week, with flexibility.

Turn business questions into clear data requirements, including the metrics, dimensions, and level of detail needed to answer them.

Build and maintain analytical data models that teams can trust and reuse.

Use SQL to explore data, investigate problems, and understand whether results make sense.

Partner with Business Operations to define and maintain consistent business metrics and reporting.

Find the root cause of data quality issues instead of simply fixing the final output, partnering with Data Engineering when needed.

Work with large, sometimes messy datasets and clearly explain assumptions, limitations, and what the data does or does not support.

Structure and document data so it can be reliably used by both people and AI tools.

Help build and maintain AI-enabled analytics and automated reporting using tools such as Databricks Genie, Claude, and Gemini.

Monitor data and AI outputs for quality and recommend improvements to models, prompts, inputs, or configurations.

Keep data definitions, models, processes, and documentation clear and up to date so others can confidently use your work.

Must-have:

You have 1–2 years of hands-on experience working with data and analytics.

You understand SQL fundamentals and can review queries, troubleshoot errors, and determine whether results make sense.

You can take an unclear business question, break it down, and identify the data needed to answer it.

You think critically about data quality and look for root causes rather than quick fixes.

You communicate findings clearly, including assumptions and limitations, so people can make informed decisions.

You’re adaptable and interested in how AI is changing analytics. You don't need to be an AI expert, but you should be comfortable learning and working with AI-enabled tools.

You can work through ambiguity, ask good questions, and use evidence to make recommendations.

Technical Skills:

SQL for data modelling, analysis, and exploration (We have been utilizing AI to help with this but you will need to be able to explain the fundamentals of SQL)

Python or R for programming and automation.

Experience working with analytical data models, reporting, or business metrics.

Tools We Use:

Databricks, Databricks Genie, Claude, and Gemini. Experience with every tool isn't required. We care more about your data foundations, problem-solving skills, and ability to learn.

Additional Requirements:

Legally able to work in Canada

Completion of a criminal background check