Data Software Engineer – Optimized Checkout Suite
| Company | Stripe |
|---|---|
| Location | Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Junior, Mid Level |
Requirements
- 2+ 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 high interest in data
- Prior experience writing and debugging data pipelines using a distributed data framework (Spark, Hadoop, Pig, etc.)
- An inquisitive nature for diving into data inconsistencies to pinpoint issues, and resolve data quality issues regardless of the cause
- Proficiency with a scientific computing language (such as Scala or Python) and SQL
- Experience with full stack development languages such as Ruby, Java, or Go, and front-end frameworks such as React
- The ability to clearly and effectively communicate cross-functionally, derive requirements and architect shared datasets
- A passion for supporting both external users and internal customers
- Strong product sense and appreciation for different user behavior and usage patterns
- Have a high quality bar, attention to detail, and you help your team deliver polished products
Responsibilities
- Identify data needs for supporting conversion and revenue optimization efforts relating to Stripe’s Optimized Checkout Suite.
- Design, develop, and own efficient and scalable data products & pipelines to enable data-driven decisions across Stripe
- Help data science & ML teams apply and generalize statistical models on large datasets to empower more intelligent decision making
- Understand business questions and determine efficient data pipelines for answering those questions
- Build and refine Stripe’s data foundations – infrastructure, pipelines, and tools to enable stakeholders working with Scala, Spark, and Airflow
- Design and build client libraries and frameworks to log events and accurately track important usage and behavior information
- Build data pipelines that track key operations & product support metrics to help measure the impact of different strategies employed by operations teams
- Integrate with experimentation infrastructure at Stripe, to enable full-funnel measurement and personalization of experiences for buyers (end users of checkout surfaces)
- Help influence, create, and maintain best practices and data standards for tooling, querying, and reporting (including correctness, consistency, privacy, and timeliness)
Preferred Qualifications
- Ability to thrive with a high level of autonomy and responsibility
- Familiarity with Artificial Intelligence and/or solving problems using Machine Learning optimization strategies.
- Experience developing data intensive applications
- Experience leading a team of or mentoring other data and software engineers
- Experience developing, participating, or influencing team or company data strategy
- Experience and familiarity with any or all of the technologies mentioned above
- Strong growth mindset with a desire to learn by tackling challenging problems