Senior Analytics Engineer, Brightwheel

• You are passionate about data and possess strong SQL, DBT, and data modeling skills
• You enjoy deep data discovery based on business problems, and want to build scalable data models to enable self-service analytics
• You have experience juggling multiple projects with shifting priorities while continuing to deliver value to the business
• You are a curious, detail oriented, self-starter who wants to take full ownership of high impact projects with visibility throughout the organization
• 4+ years of work experience as an analytics engineer, data engineer, data analyst or DBA
• 2+ years of advanced SQL scripting, within a version controlled repository
• Demonstrated ability to refactor complex SQL queries to optimize performance
• 1+ years of coding in dbt
• Excellent data discovery and analytical skills to manage complex business data requirements and data platforms without much guidance
• Strong communication skills with both business and technical stakeholders
• Track record of requirements gathering, solutioning and documenting data models
• Strong understanding of data quality and testing methodologies
• Experience monitoring and/or troubleshooting ETL pipelines within Airflow / Python

Desirable

• Brightwheel is seeking a Senior Analytics Engineer to join the Analytics team
• As an analytics engineer at Brightwheel, you will be responsible for building and maintaining the data layer for our analytics stack, top to bottom. Part data engineer, part data analyst, and part the connective tissue in-between, your responsibilities will span from raw data, up through cleaned, organized and analyzable data
• You’ll apply software engineering practices like version control, automated testing, documentation, code review and continuous integration to our data stack. In a particular week, you will find yourself:
• Writing SQL in DBT to build robust, extensible, and performant data models in a cloud-based data warehouse that will drive business intelligence for the company
• Collaborating with business users and data analysts, designing and building data models that unlock their data discovery and analyses
• Working with engineers to understand existing, complex data models and implementing new, simpler data structures to unlock business insights and data comprehension for all
• Improving organizational capacity by owning data discovery and cataloging tools that create visibility into business process, especially for non-technical users
• Troubleshooting, improving and scaling existing data models and reports