Business Intelligence and Analytics Engineer

BSc/MA in a quantitative discipline such as Computer Science, Statistics, Math, or Engineering. At least 2 years of experience in an analytics engineering, data engineering, data analytics, or a related field. Advanced experience working with data pipeline tools, particularly in-warehouse transformation tools (preferably dbt). Advanced experience with SQL. Experience querying and designing performant tables within OLAP data warehouses (e.g. Snowflake, BigQuery). At least 1 year experience working & developing with BI Tools (preferably Looker). Familiarity with frameworks and tradeoffs in building complex data models, preferably working with dimensional modeling frameworks (e.g. Kimball, Data Vault). Excellent communication (oral and written), attention to detail, time management and organizational skills. Experience and comfort using the command line. Experience using git for version control.

Act as a subject matter expert (SME) and deliver training to cross-functional teams. Deliver direct analytical insights like dashboards and ad-hoc analyses to business stakeholders. Collaborate with teams across the company to understand use cases and deliver high-value data tools. Ensure data quality and freshness at every step of the pipeline. Create reverse ETL flows to make modeled data directly to stakeholders. Define and build robust DataOps pipelines and data expectations. Explore, propose, and integrate new data sources and software solutions. Contribute to data-driven culture by training stakeholders and creating resources. Partner with data and machine learning engineers and work with a modern data stack (Airflow, FiveTran, Snowflake, dbt, and Looker).