Data Engineer



11-50 employees

Underwriting platform for insurance companies

Data & Analytics
AI & Machine Learning
Financial Services

Junior, Mid

Remote in USA

Required Skills
Data Science
Apache Kafka
Data Analysis
  • Demonstrated interest in data and machine learning for impact
  • University degree in Computer Science, Data Science, Information Systems, Data Mining, Mathematics, Statistics, Physics, Applied Sciences, or a related field
  • 2+ years of hands-on industry experience in data engineering
  • Familiarity with event backbone and job pool platforms (Kafka, etc)
  • Willingness to get hands dirty across a broad variety of internal and client software
  • Experience engaging with customers and translating customer needs to valuable features
  • 2+ years of experience with Typescript, Python (Django) and have built complex ETL pipelines
  • Hands-on experience with SQL database design, data modelling and data mining
  • Demonstrated ability to pick up new technologies quickly and learn on the spot
  • Experience in design and code reviews
  • Develop, design, create, modify, and/or test ETL pipelines or systems to support our Machine Learning and Analytics capabilities
  • Ensure quality of data through their flow, implement guardrails, health checks and alerts
  • Be able to collaborate with customers and understand in depth their data ecosystem to successfully consolidate our data models for predictive modelling
  • Develop a strong understanding of relevant data domains, codebase, and/or systems
  • Demonstrate proficiency in data engineering, data architecture, programming, and software engineering
  • Demonstrate good judgment in selecting methods and techniques for obtaining solutions
  • Work independently, use available resources to get unblocked, and complete tasks on schedule by exercising strong judgment and problem solving skills
  • Master internal development standards from developing to releasing code in order to take on tasks and projects with increasing levels of complexity
  • Collaborate with Data Science, Product Managers and Software Engineers to build robust ETL pipelines that enable the Product Support team to deliver compelling user-facing features
  • Be able to work with customer empathy in ensuring that data processes and flows support their needs

Company Stage

Series B

Total Funding



San Francisco, California



Growth & Insights

6 month growth


1 year growth


2 year growth