Model raw data into clean, tested, and reusable datasets by using dbt.
Apply various transformations (combining, cleansing, flattening, aggregation, etc.) to build a coherent foundation layer for reporting and analysis.
Ensure that SQL code is performant, well formatted and maintainable, with appropriate naming and development conventions consistently applied.
Provide identifiable and understandable descriptions of data and stages of transformation, as well as exposing them in a way for all consumers to easily find answers to their queries.
Define measure and create testing processes to ensure data is accurate enough to fit operational and analytics needs.
Apply software engineering best practices for analytics (especially in dbt) in terms of version control, testing and deployment.
Build dashboards, charts, and reports using BI tools.
Work collaboratively with all stakeholders, namely data engineers and business analysts to align our data assets with business requirements.

4 + years of experience in data transformation and modeling, Commercial experience of Kimball/Dimensional or Data Vault methodologies are highly desirable.
Experience in cloud data warehouses such as Snowflake, Redshift, BigQuery or similar.
SQL wizard.
1+ years of experience working with DBT.
Experience in building reporting layers for BI tools / experience in dashboarding.
Excellent verbal and written communication skills; ability to communicate effectively with different levels of management, as well as the business and technical communities.
Fluent in English is a must.

Senior Analytics Engineer

Key skills