CoverWallet, an Aon company, was founded in 2015 to reinvent the $100 billion small business insurance industry by using data, design, and technology. As a part of Aon, a leading global professional services firm providing a broad range of risk, retirement and health solutions with 50,000 colleagues in 120 countries, CoverWallet has the mentality and culture of a high-growth startup with the backing and support of a global multinational company.
CoverWallet is the easiest way for businesses to understand, buy, and manage insurance online and has been recognized as a CNBC Upstart 100, won the Best Insurtech Solution from the Benzinga Awards and was named “One of the Most Entrepreneurial Companies in America” by Entrepreneur Magazine.
The Analytics Engineer will be responsible for building robust analytical platforms to support data-driven initiatives across the company. You will be working closely with both our Data Analysts/Scientists and Data Engineers in order to build strong data foundations and a best-in-class platform, and will be experienced in implementing and expanding modern data workflows.
Projects you might be involved in include:
- Building out our data model using dbt (Data Build Tool) to increase the velocity of our Analytics Team creating new core data objects and data transformations to make it easier for our Data Analysts/Scientists to query, work and understand our data.
- Implementing a data quality validation process to ensure our data platform delivers accurate insights to our business stakeholders.
- Participating in the definition and development of our ETL/ELT workflows by partnering with our Data Engineering team.
Essential Job Functions:
- Partner with the Analytics and Data Engineering teams to understand problems-to-be-solved with our current data platform, identify solutions, and deliver high-quality data foundations to data stakeholders across the business.
- Create and own efficient and scalable core data objects and transformations that unify key data assets and streamline analytical workflows.
- Evolve our data platform using a modern data engineering stack, including data warehousing, data workflow platforms, data validation products, and other necessary technologies.
- Work with cross-functional stakeholders (Product, Marketing, Operations, Finance) to curate, define, and document company-wide sources of (data) truth.
- +3 years of experience in data roles with a substantial engineering component, working with modern analytics teams in high-growth, high-performance environments.
- Track record of collaborating with other data professionals and technical teams to develop a data platform, including upstream requirements, data model, desired data workflows, etc.
- Experience working with multiple data platform components, including reporting tools (Looker, Tableau, etc.) and data transformation systems (Airflow, dbt). Experience in data warehousing is a plus (such as Redshift, or Snowflake).
- Highly proficient in SQL and the ability to own data transformations
- Comfortable driving multiple stages of data tools project cycle, eg identification of data platform problems-to-be solved, solution evaluation (buy vs. build), proof-of-concept, and final solution implementation.
- Familiarity with Python or similar languages in a production environment.
- Experience working in Agile environments, preferably with Jira and Asana and ability to work in a fast-paced environment.
- Strong written and verbal communication skills (technical and non-technical)
- Strong quantitative reasoning skills and experience using data to provide insights to executive leadership and other departments.
You will receive a competitive salary and work in a highly collaborative environment. We are a fast-paced, growing firm that is the perfect place for a goal-oriented, hardworking individual who is looking to make a difference. We expect massive growth over the next few years, which means you can expect plenty of opportunities for advancement.
If all of this sounds interesting, let’s talk!