Data Analyst (Banking, ESG & Regulatory Reporting)

Quick Facts

• Role: Data Analyst (Banking, ESG & Regulatory Reporting)
• Focus: ESG data and regulatory reporting (EU Taxonomy, EBA Pillar 3 ESG, SREP)
• Primary stack: Python, PySpark, SQL, Jupyter Notebook, GitHub

Description

We are looking for an experienced Data Analyst to support ESG data and regulatory reporting initiatives within a leading global financial institution. You will contribute to the development, enhancement, and maintenance of data assets used for regulatory and sustainability disclosures, working closely with stakeholders and technical teams to ensure reliable outputs. The role combines hands-on data analysis, data transformation, and data quality investigations using Python, PySpark, SQL, and distributed processing tools.

Responsibilities

• Analyse and process large, complex datasets to support ESG regulatory reporting and disclosure requirements.
• Support development, enhancement, and maintenance of data assets for EU Taxonomy, EBA Pillar 3 ESG, SREP, and other regulatory initiatives.
• Perform data exploration, transformation, aggregation, and validation using SQL, Python, Pandas, and PySpark.
• Use Jupyter Notebook for exploratory data analysis, prototyping, testing, and validating transformations.
• Investigate data discrepancies, identify root causes, and provide actionable insights to stakeholders.
• Run data quality checks, reconciliations, and consistency assessments to ensure accurate reporting outputs.
• Collaborate with data engineers to define, implement, and optimize data transformations and ETL workflows.
• Gather and translate business/regulatory requirements into technical specifications and data transformation logic.
• Assess the impact of changing reporting requirements on existing datasets, data 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, code collaboration, and change management.
• Document data mappings, transformation rules, analytical findings, and data lineage.
• Communicate findings, risks, and recommendations clearly to both technical and non-technical stakeholders.

Requirements

• 4–5+ years of experience in Data Analysis, preferably within banking, financial services, or regulatory reporting environments.
• Strong proficiency in SQL, including complex joins, CTEs, aggregations, window functions, and data reconciliation.
• Strong practical experience with Python (Pandas for manipulation/cleaning/aggregation; PySpark for large-scale processing and validation logic).
• Hands-on experience with Jupyter Notebook for exploratory data analysis, prototyping, and data validation.
• Good understanding of Apache Spark and distributed computing concepts (DataFrame operations, partitioning, performance optimisation).
• Solid understanding of data wrangling, ETL processes, data transformations, and data quality controls.
• Experience analysing large datasets and investigating data discrepancies across multiple sources.
• Familiarity with Git/GitHub, including branching and pull requests.
• Ability to translate business requirements into technical data specifications and work with data engineering teams.
• Strong analytical thinking, problem-solving skills, and attention to detail.
• Experience collaborating with business stakeholders and cross-functional teams.
• Excellent communication skills and fluent English.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, Finance, or a related field.

Benefits

• Flexible collaboration model based on a B2B contract (hybrid; services may be provided from the Kraków office as agreed).
• Opportunity to work on strategic ESG and regulatory reporting initiatives.
• Exposure to modern data technologies, including Python, PySpark, Apache Spark, Jupyter Notebook, and distributed computing.
• Collaboration with experienced data engineers, business analysts, and regulatory reporting specialists.
• Challenging projects combining technical analysis with financial services domain expertise.
• Professional development opportunities and access to a global network of experts.