Data Analyst – Python, SQL & PySpark (Financial Services)
Core
Analyze, transform, and validate large datasets for corporate clients, focusing on data quality, ETL processes, and regulatory/management reporting.
Role type
Data Analyst (Financial Services)
Builds
Data transformations, ETL processes, and reports for regulatory and management purposes
Domain
Financial Services / Corporate Banking
Required skills
SQL, Python (Pandas), PySpark, Git, GitHub, ETL, Data Quality, Data Validation, Analytical Problem Solving
Preferred skills
ESG concepts, Regulatory Reporting (SREP, EBA), Corporate Banking, Credit Risk, Jupyter Notebook
Technologies
SQL, Python, PySpark, Git, GitHub, Pandas, Jupyter Notebook
Responsibilities
Analyze and transform large datasets using SQL, Python, and PySpark; Investigate data quality issues and identify root causes; Develop and validate ETL processes; Collaborate with data engineers and business analysts; Document data mappings and transformation rules; Support data preparation for regulatory and management reporting.
Seniority
Mid-Senior, hands-on IC