Data Analyst (Python, SQL, PySpark)

Quick Facts

• Role: Data Analyst (Python, SQL & PySpark)

• Focus: Data and regulatory reporting for corporate clients in financial services

Description

You will work on data and regulatory reporting within the corporate clients segment, handling large and complex datasets. The role combines hands-on data analysis with exposure to ESG and regulatory reporting, including investigating and resolving data quality issues.

Responsibilities

• Analyse, transform, and validate large datasets using SQL, Python, and PySpark

• Investigate data quality issues and identify root causes

• Develop and validate data transformations and ETL processes

• Work with data related to corporate clients, financial products, and reporting

• Collaborate with data engineers, business analysts, and other stakeholders

• Use Git and GitHub for version control and team collaboration

• Document data mappings, transformation rules, and analytical findings

• Support data preparation for regulatory and management reporting

Requirements

• Experience working as a Data Analyst or in a similar data-focused role

• Strong SQL skills, including joins, CTEs, aggregations, and data validation

• Hands-on Python experience, particularly Pandas

• Practical experience with PySpark and large-scale data processing

• Experience using Git and GitHub

• Experience working with large and complex datasets

• Understanding of ETL processes, data transformations, and data quality

• Strong analytical and problem-solving skills

• Good communication skills and fluent English

Benefits

• B2B contract

• Hybrid working model

• Opportunity to work on an international banking project

• Access to modern data technologies

• Collaborative working environment and professional development opportunities

• Opportunity to develop knowledge of ESG and regulatory reporting