Data Analyst (Banking, ESG & Regulatory Reporting)

Quick Facts

• Role: Data Analyst focused on ESG & regulatory reporting in financial services

Description

You will support ESG and regulatory reporting initiatives by analyzing and maintaining data assets that power disclosures such as EU Taxonomy, EBA Pillar 3 ESG, and SREP. The work includes exploring, transforming, validating, and troubleshooting complex datasets in collaboration with business stakeholders, regulatory reporting teams, and data engineering specialists. Emphasis is on Python, PySpark, SQL, and distributed data processing using tools like Jupyter Notebook and GitHub.

Responsibilities

• Analyze and process large, complex datasets for ESG regulatory reporting and disclosure requirements

• Develop, enhance, and maintain data assets for EU Taxonomy, EBA Pillar 3 ESG, SREP, and other regulatory initiatives

• Perform data exploration, transformation, aggregation, and validation (SQL, Python, Pandas, PySpark)

• Use Jupyter Notebook for exploratory data analysis, prototyping, testing, and validating transformations

• Investigate data discrepancies, identify root causes, and provide actionable insights

• Execute data quality checks, reconciliations, and consistency assessments

• Collaborate with data engineers to define, implement, and optimize data transformations and ETL workflows

• Translate business and regulatory reporting requirements into technical specifications and transformation logic

• Assess the impact of changing reporting requirements on datasets, pipelines, and deliverables

• Work with large-scale datasets in Apache Spark and distributed computing environments

• Support testing, validation, and implementation of new or enhanced data solutions

• Use GitHub for version control, collaboration, and change management

• Document data mappings, transformation rules, analytical findings, and data lineage

• Communicate findings, risks, and recommendations to technical and non-technical stakeholders

Requirements

• 4–5+ years of data analysis experience

• Banking, financial services, or regulatory reporting experience preferred

• Strong proficiency in SQL (joins, CTEs, aggregations, window functions, reconciliation)

• Strong practical experience in Python (Pandas, PySpark)

• Hands-on experience with Jupyter Notebook for exploratory analysis and validation

• Understanding of Apache Spark and distributed computing concepts (DataFrames, partitioning, performance optimisation)

• Experience with data wrangling, ETL, data transformations, and data quality controls

• Experience investigating data discrepancies across multiple sources

• Familiarity with Git/GitHub workflows (branching, pull requests)

• Ability to translate business requirements into technical data specifications

• Excellent analytical thinking and attention to detail

• Ability to communicate clearly with technical and non-technical stakeholders

• Fluent English (written and spoken)

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Finance, or related field

Benefits

• Flexible B2B collaboration model

• Opportunity to work on strategic ESG and regulatory reporting initiatives for a leading global financial institution

• Exposure to modern data technologies (Python, PySpark, Apache Spark, Jupyter Notebook, distributed computing)

• Collaboration with data engineers, business analysts, and regulatory reporting specialists

• Challenging projects combining data analysis with financial services domain expertise

• Collaborative and supportive team environment

• Professional development opportunities and access to a global network of experts