
Senior Analytics Engineer
- San Francisco, CA Los Angeles, CA
- Permanent
- Full-time
- Own and improve our dbt implementation and data models, turning raw data into scalable, business-ready datasets that enable clear analysis of business and platform performance.
- Collaborate with partners across technical and non-technical teams to bridge the gap between data and action
- Inform key decision makers about the state of the business through internal data products
- Own the development, testing, documentation and evangelism of our core data models
- Utilize analytical tools such as Databricks, BigQuery, Airflow, Mode and Tableau to help our business and data science partners to build actionable insights
- Develop strong cross-functional partnerships across Calm to drive success
- Partnering with Data Engineering to set up a reporting system in BigQuery from scratch. This included data replication, infrastructure setup, dbt model creation, and integration with reporting endpoints
- Developing and implementing an alerting system for critical metrics
- Architecting the data warehouse to serve many internal data consumers (e.g. analysts, engineers, product managers, operations managers)
- Building an efficient and scalable data pipeline for high-volume events in the data warehouse
- Extensive experience with data modeling and analyzing large scale data with modern cloud computing platforms. Experience with dbt strongly preferred
- Strong proficiency in SQL
- Experience with data pipeline development tools in a modern data stack such as dbt, Databricks, BigQuery, and Airflow
- Prior experience in Python
- Ability to translate non-technical business requirements into technical solutions, and translate technical solutions to business outcomes
- Strong relationship management and presentation skills
- Hands-on experiencing building data documentation and testing practices
- Pragmatism: balancing scrappiness and rigor
- Prior work experience in a subscription business or B2B SaaS
- Experience working with tools in a data lake architecture (e.g. Spark)
- 8 years of relevant experience
- 4+ in data science, data engineering or analytics engineering
- Strong proficiency in SQL