About the position
Lula is a Series A, VC-backed insurtech startup based in Miami, FL, US that is revolutionizing the insurance industry by rethinking how insurance is priced, sold, and managed. They prioritize their identity as a tech company first and an insurance company second. Their goal is to upgrade the insurance industry's infrastructure to enable seamless integration of insurance into businesses, similar to payment processing. As a Data Engineer, you will be responsible for designing and building Lula's Data Platform, creating reliable and efficient data pipelines, optimizing data models, and influencing logging practices to support data flow. With at least 8 years of experience in data engineering, you will play a crucial role in shaping Lula's data infrastructure.
Responsibilities
- Design and build LULA's Data Platform used by insurance and product teams
- Build data pipelines that are reliable, efficient, testable, and maintainable
- Design data models for optimal storage and retrieval and to meet critical product requirements
- Understand and influence logging to support data flow and architect logging best practices where needed
- Bring at least 8 years of experience in data engineering
Requirements
- Design and build LULA's Data Platform used by insurance and product teams
- Build data pipelines that are reliable, efficient, testable, and maintainable (with Fivetran, Talend, Matillion, Apache Airflow or similar)
- Design data models for optimal storage and retrieval and to meet critical product requirements
- Understand and influence logging to support data flow and architect logging best practices where needed
- At least 8 years of experience in data engineering
Benefits
- At least 8 years of experience in data engineering
- Technologies (dbt, BigQuery, Redshift, Postgres)
- Proficiency with Python
- Experience with custom ETL/ELT and programming/scripting language experience
- Demonstrated experience using a data visualization tool such as Looker or Tableau to visualize and model raw data sets
- Experience building and optimizing data pipelines, architecture, and data sets
- Experience designing and deploying high performance systems with reliable monitoring and logging practices.
- Previous experience in a fast-paced startup environment