Design and build scalable and resilient Data & Analytics solutions
Automate data workflows and optimize data processing for performance and cost
Design and development of new data pipelines
Improvement of existing data pipelines by using data engineering best practices
Design and develop efficient, scalable data models that enable fast and accurate reporting while minimizing cost and query complexity
Monitor and optimize data warehouse costs
Engage in proof of concepts and experiments
Participate in overall testing and production maintenance
Work closely with the BI Team and Architecture team to ensure smooth transition from GBQ to Snowflake

Bachelor's degree in Computer Science, Data Engineering, Data Science, Software Engineering or similar
1+ years of related work experience
Strong knowledge of Python and SQL with a minimum of 1+ years of practical experience in data automation
Ability to write efficient and scalable code for data processing
Hands-on experience with Snowflake, including performance tuning
Understanding of GBQ is a plus
Solid understanding of designing and optimising data pipelines and data models in a cloud environment
Experience in setting up ETL processes, knowledge of dbt is a plus
Expertise in working with scalable data architectures, including data warehouses, data lakes, and data pipelines
Experience with BI tools like Looker, Tableau, Sigma or similar is a plus

Data Analytics Engineer

Key skills