Must Have:
- Strong BI / analytics engineering foundations — designing reporting data models, applying data governance, and translating business logic into testable, maintainable data products.
- Hands-on experience producing regulatory reports in financial services — PSP, acquiring, banking, AML/CFT, or similar. Direct exposure to central bank or financial regulator submissions is a strong plus.
- Strong cloud data warehouse skills — advanced SQL, query and resource performance tuning, comfort with the security and object model of a modern cloud DWH (Snowflake, BigQuery, Redshift, Databricks, etc.).
- dbt — building models, writing tests and macros, data contracts.
- Python, including the ability to build lightweight data-facing applications (Streamlit or a comparable framework).
- 3+ years in data engineering, analytics engineering, or BI development on a modern cloud warehouse.
- Ability to read regulatory specifications (templates, taxonomies, dataset definitions, deadlines) and turn them into data lineage, transformations, and acceptance criteria.
- End-to-end ownership under ambiguity — proven track record of turning vague requirements into validated, production-grade deliverables, driving alignment across multiple counterparties without close supervision.
- Advanced English.
- Bachelor's degree in a quantitative field.
Nice to Have:
- BI tools (Tableau, Power BI, etc) for ad-hoc reporting alongside the Streamlit platform
- Cloud infrastructure exposure (AWS / Azure / GCP)
- Prior consulting experience in financial services data
- Hands-on experience with Git, CI/CD, IaaC
- AI-assisted and agentic development