Some of the things you ll be doing:

• Working closely with Analysts Data Scientist to understand business requirements and provide data ready for analysis

• Designing high-performance, reusable, and scalable data models for our data warehouse to ensure our end-users get consistent and reliable answers when running their own analyses

• Writing complex yet optimised data transformations in SQL using dbt

• Scheduling data transformation and analysis pipelines using airflow

• Continuously discover, transform, test, deploy and document data sources

• Applying, help define, and champion data warehouse governance: data quality, testing, coding best practises, and peer reviews

• Applying advanced aggregations and data wrangling techniques such as imputation for predictive analytics

• Keeping our data efficient and consistent at a global level, maintaining our warehouse environments over multiple regions

• Working with Snowflake, dbt, Apache Airflow, Python, Fivetran, AWS, git and Looker

What you ll get in return:

• Competitive Salary

• Family health insurance

• Life and Accidental Insurance

• 25 days annual holidays

• Special Dental Allowance

• We invest in your development with professional LD budget (fixed amount per year)

• Stock options

You ll be a great fit if:

• Strong hands-on data modeling and data warehousing skills and passion (our data warehouse is based on Snowflake, with transformations orchestrated through dbt)

• Experience in dimensional modelling, specifically designing, developing and maintaining STAR and/or snowflake schemas

• Experience with SDLC within a Data Warehouse context, including experience using Git and familiarity with Continuous Integration and Deployment

• Extensive experience in SQL query optimization troubleshooting

• Power-user expertise in at least one of these Cloud technologies: Snowflake, AWS, Google Cloud, Microsoft Azure

• Solid experience with ETL and scheduling tools (e.g. Talend, Airflow)

• Experience with data visualization tools and packages (e.g. Looker, Tableau, matplotlib)

• Strong attention to details to highlight and address data quality issues

• Proven project management skills: roadmap, prioritisation, and stakeholders management

• Strong communication skills to work with non technical stakeholders and an excellent understanding of the commercial value of their work and the monetisation of data.

• Ability to deal with ambiguity and competing objectives in a fast paced environment