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Wealthsimple // online investment manager
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Wealthsimple is on a mission to help everyone achieve financial freedom, no matter who they are or how much they have. Using smart technology, Wealthsimple takes financial services that are often confusing, opaque & expensive & makes them simple, transparent, & low-cost. We're the company behind some of Canada's leading digital financial products, & are growing faster than ever.

Our team is reimagining what it means to manage your money. Smart, high-performing team members will challenge you to learn & grow every day. We value great work & great ideas - not ego. We're looking for talented people who love a fast-paced environment, & want to ship often & make an impact with groundbreaking ideas.

We're a remote-first team & output is more important than face time, so where you choose to work is up to you - as long as you have internet access, you can work from anywhere in Canada. Be a part of our Canadian success story & help shape the financial future of millions - join us! Read our Culture Manual & learn more about how we work.

At Wealthsimple, we are building products for a diverse world & we need a diverse team to do that successfully. We strongly encourage applications from everyone regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status. Wealthsimple provides an accessible candidate experience. If you need any accommodations or adjustments throughout the interview process & beyond, please let us know.

The Data Science & Engineering (DSE) team consists of analytics engineers, data scientists & software engineers with diverse educational backgrounds such as math, operations research, economics, computer science, engineering & business. The team is responsible for enabling data-driven decision making & building data products at Wealthsimple.

We achieve these goals by:

Building a high quality & scalable state-of-the-art data warehouse that powers all decision making
Leveraging machine learning & algorithms to help Wealthsimple build smarter financial products
Using decision science to understand the cause & effect of our business decisions

About the role

We are hiring for an Analytics Engineer on the Operations Data Science Team. As an Analytics Engineer, you will be at the intersection of business & product teams, data scientists & data engineers. You will be responsible for building robust, efficient & integrated data models that enable analytics & machine learning across the company. You will play a critical role in building the source of truth in the data warehouse. The successful Analytics Engineer is able to blend business acumen & software engineering best practices while effectively communicating with stakeholders.

This particular role is on the team that supports the our operations team (financial-operations, customer-experience-operations, etc..), which provides a comprehensive & data-driven view on how their area of the business is doing. In this role, you will build the data models & metrics that WS leaders will use to understand & analyze the inputs & outputs of their respective domains. You will have a critical & comprehensive impact on how WS uses data to make better decisions

In this role, you will have the opportunity to:

Build data models in cloud data warehouse that will be used as the source of truth for analytics across the company
Apply software engineering best practices like version control & continuous integration to the analytics code base
Translate business requirements into data models that will help stakeholders answer key business questions
Ensure data models are well tested, documented & maintained
Believe that simple is better, Occam's razor is your friend
Take ownership & ship it
You release incrementally & iteratively
Get the best out of the team by leveraging their diverse educational backgrounds
Teach & learn from their teammates. We value making others successful

Skills we are looking for:

Excellent SQL
Experience with dbt
Comfortable with software engineering best practices like version control & using Git
Experience with a cloud data warehousing (Snowflake, Bigquery, Redshift)
Proficient understanding of data warehousing methodologies & concepts (Kimball, Inmon, etc)
Experience working as part of a data team; either a data analyst, data scientist, or data engineer
Able to build & maintain multi-functional relationships with various teams across the business
Excellent communicator who is able to translate business requirements into data models & maintain clear
Knowledge of another programming language e.g. Python is a plus
Fivetran or Stitch for data extraction & loading as Plus
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