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Senior Data Analyst

Remote:

Full Remote

Experience:

Senior (5-10 years)

Work from:

California (USA), United States

Offer summary

Qualifications:

8+ years experience in analytics engineering, Strong SQL and programming skills.

Key responsabilities:

Support cross-functional teammates with analysis
Design dashboards, perform adhoc analysis
Create reusable code artifacts, maintain data transformations
Design and implementation of tools for data quality

Step Financial Services Scaleup https://www.step.com/

51 - 200 Employees

See more Step offers

Job description

Gen Z is the generation of the side hustle. 💪🏻 They’re creators. 👩‍🎤 They’re freelancers. 🧑‍💻 They’re investors. 👩‍💼 And they’re not afraid to take on challenges, especially when it comes to their finances - and we’re here for it.

Step is a next-generation financial services company building a better banking experience to help teens and young adults achieve financial independence and knowledge at an earlier age. We’re on a mission to improve the financial future of the next generation by empowering teens to start their financial journey today. Step is a well-funded Series C company that has raised more than $175M, focused on disrupting the banking industry through a differentiated mobile-first consumer experience.

Teens and families love our product. We eclipsed 1 million customers in just four months after launch and have now crossed 4 million customers. If you’re looking to join a fast-growing company with a strong mission and vision that puts people first, we want to meet you!

The role

We seek an experienced Senior Data Analyst to enable and accelerate Step’s Data Analytics and Data Science projects.

What you'll do

Support all cross-functional teammates for end-to-end analysis on key initiatives.
Design and build dashboards to track business, product, and risk metrics.
Perform adhoc analysis to understand business and customer trends.
Design, create and maintain data transformations to produce reusable and efficient datasets for data analytics and data science use cases.
Create reusable code artifacts to enable, accelerate and improve the work of data analysts.
Model, create and maintain data in our self-serve BI tools.
Design, create and maintain data pipelines.
Create reusable query and visualization components in our BI tools.
Design and implement tools to ensure data quality and freshness.