We are seeking a highly technical Data Warehouse Engineer with deep expertise in database administration and data transformation. This role is crucial for building and maintaining the foundation of our data stack, focusing on data warehouse development and performance optimization. You will be responsible for architecting relational data models, ensuring database performance, and building clean, reliable data sources that agnostically power BI products (Looker Studio, Power BI, Tableau etc). Your expertise will be vital in creating a high-performance, well-documented, and scalable data warehouse.
Develop, manage, and optimize our entire data transformation layer using dbt, ensuring models are efficient, tested, and well-documented.
Design and implement robust, scalable data models using data warehousing strategies (Star Schema, Snowflake Schema).
Collaborate directly with BI developers and analysts to build and optimize data sources for various dashboard design tools (e.g., Looker Studio, Looker, Power BI).
Write and maintain DDL and DML scripts, manage database migrations, and enforce data quality standards.
Manage our dbt project in source control (GitLab/GitHub), managing branching and CI/CD pipelines.
SQL & Query Optimization: Mastery of advanced SQL (DDL, DML) and the ability to interpret and act on EXPLAIN plans to tune performance.
Data Warehousing Concepts: Strong, practical knowledge of relational databases and data warehousing strategies (Star Schema, Snowflake Schema).
Postgres Features: Proven experience with advanced PostgreSQL features, including partitioned tables, views, and materialized views.
BI Data Modeling: Strong experience designing data models to support general dashboard design tools (Looker Studio, Looker, Power BI, etc.).
GitLab/GitHub: High level of competency in using Git for version control, especially for managing a dbt project.
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