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Analytics Engineer (Mid/Senior)

Clearcover LogoClearcover
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Our Value Proposition: Clearcover is a venture-backed technology start-up disrupting the trillion-dollar legacy insurance market. We’ve focused on building products that create confident, happy customers - and we’re flourishing. We believe in putting our people first, paying them well, and working together to solve tough problems. If you’d like a high-growth opportunity with an award-winning company, let’s chat.

In this role:

The Analytics Engineer works closely with data engineers, data analysts and data stakeholders to deliver tested and documented datasets to various data domains at Clearcover. These datasets enable our stakeholders to make effective decisions and answer questions in a self-serving manner. The ability to speak the language of a business user while applying technical prowess is key to this role.

What will you do?

  • Own and maintain all analytic data models sourced from various production systems in our data warehouse
  • Design and optimize our cloud-based data warehouse architecture
  • Write production-quality ELT/ETL data transformation code with an eye towards performance, maintainability, and scalability
  • Design, build, and maintain data pipelines to ensure reliable business reporting
  • Advocate for improvements to data quality and performance
  • Collaborate with data engineers on infrastructure projects for sourcing data
  • Responsible for delivering new, re-usable business intelligence solutions and demonstrating value proposition to business stakeholders
  • Work with data stakeholders to develop approaches in finding, collecting, and using data

What do you need?

  • Strong written and verbal communication skills including the ability to collaborate across teams
  • Significant experience developing and delivering data solutions as a member of a business intelligence or analytics team
  • Have a passion for solving problems using data and analytics
  • Must have a solid understanding of data warehouse architecture and best practices
  • Deep understanding of SQL, writing complex queries and/or stored procedures in current role
  • Have used Python, Ruby, or R when SQL failed you or was needed for a complex report or analysis
  • Experience with Snowflake, BigQuery or other Cloud Data Platforms serving as a production Data Warehouse
  • Experience with Looker or other data visualization tools (Tableau, Superset, PowerBI)

What’s nice to have?

  • Experience with dbt (Data Build Tool)
  • Experience with version control tools (Github, Bitbucket)
  • Experience working with semi-structured data types such as JSON and XML
  • Experience in Property and Casualty insurance industry