Analytics Engineer II
Remote - US
About the team & opportunity
What’s so great about working on Calendly’s Engineering team?
We make things possible for our customers through innovation.
Why do we need you? Well, we are looking for an Analytics Engineer to join our fast-growing organization who will bring experience developing data models built for the present and the future, a keen eye for reliability and performance, and is a team player.
A day in the life of an Analytics Engineer at Calendly
You will reside on the Analytics Engineering (AE) team with a focus on building robust and scalable analytical insights. These models, built on Google's BigQuery, will be leveraging data build tool (dbt) and follow engineering best practices. The role is part of a team that ensures the organization has access to timely, accurate, relevant, and proactively persuasive insights to efficiently grow the business.
In this role, you will develop and maintain the enterprise data models used to support and drive the growth of Calendly. You will be an influential member of the AE team to help deliver high-quality data assets that enable data-driven decisions while ensuring data accuracy and consistency. You should have a drive for supporting the business, asking the right questions, and delivering an analytics layer that will push Calendly forward - all while helping shape the team.
On a typical day, you will be working on:
- Creating tremendous business value from the various data sources within our data warehouse
- Developing the analytics layer in the data warehouse
- Working closely with business leaders and analysts to understand their needs and deliver sustainable data assets used to power visualizations and insights
- Managing performance and accuracy of data transformations to build and maintain trust in our data
- Identifying opportunities for data model consolidation and/or optimization
- Contributing technically and culturally to the growing AE team
What do we need from you?
- Strong analytical SQL skills with a keen eye for detail and data accuracy - experience with another analytical language is a bonus (e.g. R or Python)
- Exposure to a dbt project that leverages engineering best practices (e.g. data quality tests, unit tests, etc)
- Exposure to version control systems like GitHub to maintain a codebase and provide feedback through code reviews
- Experience with data modeling to serve business stakeholders’ needs
- Strong ability …
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Authorized to work lawfully in the United States of America
Tasks- Data modeling
Analytical Analytics Analytics engineering BigQuery Data Modeling Dbt Engineering GitHub Privacy Python R SQL
Education TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9