- Strong hands-on knowledge of SQL and/or Python for data analysis and ad hoc query development.
- Valuable understanding of ETL processes and the ability to translate designs into dimensions and facts while considering source change data capture.
- Experience with cloud data warehouse technologies such as Snowflake is preferred.
- Understanding of data modelling for data science projects, particularly working with large historical snapshot tables and multiple features.
- Fast learner with the ability to evaluate emerging technologies and design scalable, distributed data architectures.
- Design and implement scalable data pipelines and architectures in Snowflake, optimising data flow for cross-functional teams.
- Develop and optimise complex SQL queries and scripts to support data transformation, aggregation, and analysis.
- Ensure data security and compliance measures are implemented in line with industry standards and regulations.
- Strong understanding of data modelling principles and best practices.
- Experience with Snowflake data warehousing, including architecture, management, and Snowpipe.