About The Team
- The Stripe People Analytics team is looking for a data engineer with a passion for building scalable, secure, data foundations to join the team. Your mission will be to develop and provide data solutions necessary to enable people data scientists and analysts across Stripe to build a deeper understanding of Stripe’s workforce.
What you’ll do
- You will be responsible for the design, build, and deployment of structured data pipelines, storage, and model schemas to enable scaled self-service analytics.
- You will leverage modern performance tuning techniques, conceptual schemas, and modern technology to transform Stripe’s raw employee data into high-performing structured models that empower the internal customers to be data-driven.
- You will be accountable to identify, define, protect, and manage data from its raw form to its consumption and work collaboratively across product teams, data analysts, data scientists, and technology teams.
- Identify data needs for the people team and people-focused teams across Stripe, understand specific requirements for metrics and analysis, and build efficient and scalable data pipelines to enable a science-driven people function
- Design, develop, and maintain critical database infrastructure, data sets, and pipelines
- Ensure data is stored safely and securely, conforming to frequently changing international regulations (e.g. GDPR) and best practices around people data storage and security
- Own critical data pipelines and manage the SLAs for those data pipelines, and constantly improve pipeline efficiency and data quality
- Facilitate data integration and transformation requirements for moving data between applications; ensuring interoperability of applications with database, data warehouse, and data mart environments
- Assist with the design and management of the technology stack used for data storage and processing
- Contribute to the development and education plans on data engineering capabilities, systems, standards, and processes
Who you are
Stripe’s 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.
- 5+ years of experience in a Data Engineering role, with a focus on building scalable storage and schema layers
- Expertise in a programming language such as Python or Scala, and their respective standard data processing libraries
- Experience with writing and debugging data pipelines using a distributed data framework (Hadoop/Spark/Pig etc…)
- Strong experience in relational databases (AWS, RDS, Aurora), SQL, data warehouses, and ETL pipelines
- Experience in integrating data from core platforms into a centralized warehouse
- Rigor in high code quality, automated testing, and other engineering best practices
- Understanding and experience with building secure systems and access models for highly sensitive data
- The ability to communicate cross-functionally, derive requirements, and architect shared datasets
- Delight in building great tools that are a joy to use
- Previous experience at a quickly-scaling or large company
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1