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Staff Software Engineer

3 months ago

San Francisco, United States 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

With all this data, the Data Science team builds data and intelligence into our product, sales, and operations. This spans from building data foundations, to applying statistical techniques and machine learning to measure and optimize our data-driven products, to rapid in-depth analysis that inform Stripe’s strategic decisions.

What you’ll do

We’re looking for a hands-on person with a strong background and demonstrated leadership in building data applications. As a Staff Engineer you’ll be empowered to make decisions with a significant impact on Stripe, and help guide our investments and strategy while making our data reliable, secure, and a delight to use. 

You will be a key contributor to the next-generation of our metrics platform, with a core charter to make it easier for Stripe to build and operate high-quality metrics. We are in the midst of a multi-year journey to revamp our data warehouse by placing high-quality data at the core, by design. Metrics platform is the part of this core vision, and you will make a step-function difference in our ability to empower Product, Engineering, and Science teams and have an impact on the decision Stripe makes every day.

Staff Engineers at Stripe are empowered to operate autonomously and are counted on to help drive Stripe forward.

Responsibilities
  • Work closely with various cross-functional teams to develop and deliver tools or data structures to measure, optimize and scale our product offerings
  • Perform all of the necessary data transformations to serve products that empower data-driven decision making.
  • Engage with internal data platform and tooling teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.
  • Arbitrate critical decisions correctly considering data best practices, system realities, and numerous stakeholder’s feedback.
  • Scope, design and implement solutions that make the appropriate tradeoffs between resiliency, durability, and performance while maintaining a high level of data quality.
  • Mentor and develop other technical leaders; creating opportunities for those around you.
  • Contribute to engineering innovations that fuel Stripe’s vision and mission.
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
  • 5+ years of experience working on a large scale data warehouse and/or experimentation, personalisation, or targeting platforms.
  • Strong written and verbal communication skills with a talent for precise articulation of end-users’ problems.
  • Strong track record of making forward progress in the face of ambiguity by working with users to draw our product requirements.
  • Experience planning and driving large projects involving multiple stakeholders across an organization.
  • Strong coding skills in Scala, Python, Java, or another language for building highly performant services.
  • A mature understanding of the software development life cycle, which they can bring to bear to balance long term architecture and pragmatic solutions on a case-by-case basis.
Preferred qualifications
  • Experience with data modeling, ETL (Extraction, Transformation & Load) concepts, and patterns for efficient data governance.
  • Strong understanding and practical experience with systems such as Hadoop, Spark, Presto, Iceberg, and Airflow.
  • Strong understanding in data platform fundamentals including: clustering, distributed systems, fault tolerance, networking, etc.
  • Experience in either the front-end or back-end development of data-powered applications.