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 and expensive and makes them simple, transparent, and low-cost. We're the company behind some of Canada's leading digital financial products, and 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 and grow every day. We value great work and great ideas — not ego. We're looking for talented people who love a fast-paced environment, and want to ship often and make an impact with groundbreaking ideas.

We’re a remote-first team and 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 and help shape the financial future of millions — join us! Read our Culture Manual and learn more about how we work.

At Wealthsimple, we are building products for a diverse world and 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 and beyond, please let us know.

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

Building a high quality and scalable state-of-the-art data warehouse that powers all decision making

Leveraging machine learning and algorithms to help Wealthsimple build smarter financial products

Using decision science to understand the cause and effect of our business decisions

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 and product teams, data scientists and data engineers. You will be responsible for building robust, efficient and integrated data models that enable analytics and 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 and 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 and data-driven view on how their area of the business is doing. In this role, you will build the data models and metrics that WS leaders will use to understand and analyze the inputs and outputs of their respective domains. You will have a critical and comprehensive impact on how WS uses data to make better decisions

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 and 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 and maintained

Believe that simple is better, Occam's razor is your friend

Take ownership and ship it

You release incrementally and iteratively

Get the best out of the team by leveraging their diverse educational backgrounds

Teach and learn from their teammates. We value making others successful

Excellent SQL

Experience with dbt

Comfortable with software engineering best practices like version control and using Git

Experience with a cloud data warehousing (Snowflake, Bigquery, Redshift)

Proficient understanding of data warehousing methodologies and concepts (Kimball, Inmon, etc)

Experience working as part of a data team; either a data analyst, data scientist, or data engineer

Able to build and maintain multi-functional relationships with various teams across the business

Excellent communicator who is able to translate business requirements into data models and maintain clear

Knowledge of another programming language e.g. Python is a plus

Fivetran or Stitch for data extraction and loading as Plus