Software Engineer, Growth Data Engineering

5 months ago

Toronto, Canada Stripe Full time

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. 

About the team

Stripe is the best software platform for running an internet business. We handle billions of dollars every year for hundreds of thousands of businesses around the world. One third of Americans bought something on Stripe in the last year.

With all this data, the Growth Data Engineering team is looking for talented data-minded engineers to help us manage business critical data leveraged across the entire organization. If you are passionate about data, excited about designing data pipelines and data-driven user experiences, and motivated by having an outsized impact on the business, we want to hear from you.

What you’ll do

Every record in our data warehouse is vitally important for the businesses that use Stripe, so we’re looking for people with a strong background in data engineering and analytics to help us scale while maintaining correct and complete data. You’ll be working with a variety of internal teams across Growth, Sales, Marketing, and Data Science to help them solve their data needs. Your work will provide teams with visibility into how Stripe’s Growth organization is performing and how we can deliver a better experience to Stripe's customers.

Responsibilities

Identify data needs for Growth, Sales, and Marketing teams, understand their specific operational and reporting requirements, and build efficient and scalable data products & pipelines to enable data-driven decisions across Stripe
Design, develop, and own data pipelines, models, and products that power Stripe’s Growth, Sales, and Marketing teams
Help the Data Science team apply and generalize statistical and econometric models on large datasets to empower more intelligent decision making among our Growth & Go-to-Market teams
Develop strong subject matter expertise and manage the SLAs for both data pipelines and full stack web applications that support the Growth & Go-to-Market organizations at Stripe
Build Stripe's Customer Engagement Data Service - collecting, curating, mastering, enriching, and presenting a single view of user interactions with Stripe for consumption by data applications across the company
Build and refine Stripe's data foundations - infrastructure, pipelines, and tools to enable Growth, Sales, and Marketing teams at Stripe - working with Scala, Spark, and Airflow
Design and build client libraries and frameworks to log events and accurately track the behavior of users interacting with our logged-out user interfaces such as Stripe.com
Refine our existing data marts that help the Sales and Marketing organization at Stripe forecast the future potential performance of the business, and reliably measure their ongoing attainment toward targets
Build data pipelines that track key GTM product metrics, and measure the impact of different GTM strategies employed by teams in the field
Integrate different parts of our experimentation infrastructure at Stripe, to enable full-funnel measurement and personalization of experiences spanning from Stripe.com into product
Our stack spans tools in Spark, Scala, Python, SQL, Presto, Airflow, AWS, Java, Go, and React

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

3+ years of experience in a Data Engineering or Software Engineering role, with a focus on building data pipelines, or applications powered by big data.
A strong engineering background and are interested in data
Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Pig etc)
An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
Knowledge of a scientific computing language (such as Scala or Python) and SQL
Experience with full stack development languages such as Java or Go, and front-end frameworks such as React
The ability to communicate cross-functionally, derive requirements and architect shared datasets

Hybrid work at Stripe

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

Pay and benefits

The annual salary range for this role in the primary location is C$134,400 - C$201,600. This range may change if you are hired in another location. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and specific location. Applicants interested in this role and who are not located in the primary location may request the annual salary range for their location during the interview process.

Specific benefits and details about what compensation is included in the salary range listed above will vary depending on the applicant’s location and can be discussed in more detail during the interview process. Benefits/additional compensation for this role may include: equity, company bonus or sales commissions/bonuses; retirement plans; health benefits; and wellness stipends.

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