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Added 2 mins ago
AS
Technical Product Manager - Digital Channel Applications
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- Full-time
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This information was provided by the employer; it was not verified by Job Bank.
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Article

Data Analytics Specialist

1010 Raymur Avenue, Vancouver, BC, V6A 3T2, Canada

$73,000 to $82,000 CAD / year · Full-time

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Job details

Pay: $73,000 to $82,000 CAD / year
Job type: Full-time
Experience: You have 1–2 years of hands-on experience working with data and analytics.
Posting language: English
Posted: Sep 11, 2026

Original job description

Data Analytics Specialist

Department: Business Intelligence + Analytics

Employment Type: Permanent - Full Time

Location: Vancouver

Reporting To: Nelson Tsuboi

Compensation: CA$73,000 - CA$82,000 / year

Description

Hi there, we’re Article. 👋 Since 2013, we have been redefining the furniture industry one sofa at a time, it’s not easy - it requires solving challenging, meaningful problems. This is where you come in, as a Data Analytics Specialist (internally known as a Business Analyst), you'll turn complex data into clear, trusted insights that help our teams make better decisions.

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.

What You’ll Do

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.

Who You Are

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

Perks & Benefits

Wealth:

The salary range is $73,000 to $82,000
- Starting salary is determined by your transferable skills, knowledge, work experience, and the hiring team’s budget, which is based on business needs, market compensation data, and internal equity
We believe in Winning Together. When Article hits its annual financial goals, eligible employees will receive a cash bonus
4% RRSP matched contributions through Wealthsimple

Life:

15 days of vacation*
1 extra day off (Inclusion and Diversity Day)
6 well-being (sick) days
Hybrid work: 3 days a week in the office
Work remotely (anywhere in the world) for up to 3 weeks

Total Health:

Excellent extended health, dental and vision benefits
$1000 health/lifestyle spending account* for your total physical and mental well-being
TELUS Health App
- Mental Health Assistance/Counseling
- Virtual medical appointments

Office Space:

The Article HQ is a converted warehouse, with an open accessible layout and no offices (even for our founders)
Work from your desk, an Article sofa, collaboration spaces, or a private meeting room
- Standup desks can be requested too
Our kitchens are stocked with salty, sweet and healthy snacks, & all the premium coffees and teas to keep you buzzing
Onsite fitness equipment with showers and towel service
Pickleball, badminton, and table tennis matches happen, from very competitive to very casual
A dog-friendly office - well-socialized pups are welcome

Getting here:

Free street parking (first come, first serve; no reserved spots for senior leaders)
Indoor secure bike storage with change rooms and showers
20-minute walk to either Main Street- Science World or VCC Clark Skytrain stations

Extra:

45% discount on our entire product range (15% for friends and family)

*Prorated

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More about this job

Responsibilities

The Data Analytics Specialist will turn complex business questions into structured data requirements and build trusted analytical models. They will also monitor data quality and support the integration of AI tools into analytics workflows.

Requirements

Candidates must have 1-2 years of hands-on experience with data and analytics, including strong SQL fundamentals. Proficiency in Python or R and the ability to work through ambiguity are also required.

Skills

SQL
Data modeling
Data analysis
Python
R
Business metrics
Data quality
Reporting
Problem solving
Critical thinking
Communication
AI-enabled tools
Data operations
Automation

Benefits

Cash bonus
4% RRSP matched contributions
15 days of vacation
Inclusion and Diversity Day
6 well-being sick days
Extended health benefits
Dental benefits
Vision benefits
$1000 health/lifestyle spending account
Mental health assistance
Virtual medical appointments
Snacks and premium coffee
Onsite fitness equipment
45% product discount

Visa sponsorship

Not detected in the job text

Hiring contact

Nelson Tsuboi

Keywords

Data Analytics
Business Intelligence
SQL
Python
R
Databricks
Databricks Genie
Claude
Gemini
Data Modeling
Data Quality
Business Metrics
Automation
AI
Reporting
Data Operations
Root cause analysis
Analytical data models

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