Data Analyst – Python, SQL & PySpark (Financial Services)
Summary
Consultant data analyst supporting ESG and regulatory reporting for a global financial institution: analysing, transforming and validating large datasets for EU Taxonomy, EBA Pillar 3 ESG and SREP disclosures. Core stack is SQL, Python (Pandas, PySpark), Apache Spark, Jupyter Notebook and GitHub; B2B, hybrid from Warsaw/Kraków.
Data Analyst – Python, SQL & PySpark (Financial Services)
About Capco
Capco is a global technology and management consultancy specialising in financial services. We work with leading banks on data, technology, and transformation projects.
The Role
We are looking for an experienced Data Analyst to join an international project for a leading global bank.
The project focuses on data and regulatory reporting within the corporate clients segment.
You will work with large and complex datasets, analyse and transform data, investigate data quality issues, and collaborate closely with business and technical teams.
The role combines hands-on data analysis with exposure to ESG and regulatory reporting.
Familiarity with ESG concepts would be beneficial, while the key requirements are strong data analytics skills and a willingness to further develop knowledge in this area.
What You’ll Do
- Analyse, transform, and validate large datasets using SQL, Python, and PySpark.
- Investigate data quality issues and identify their 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.
What We’re Looking For
- 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 experience with Python, 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.
Nice to Have
- Experience in banking or financial services.
- Understanding of ESG, regulatory reporting, SREP, or EBA reporting.
- Knowledge of corporate banking, credit risk, or financial exposures.
- Experience with Jupyter Notebook or Prophecy.
What We Offer
- 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.
Recruitment Process
- Recruiter screening
- Capco technical interview
- Client interview
- Feedback and offer
Location: Kraków or Warsaw - hybrid model, with office attendance depending on project needs.
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Skills
As published by greenhouse · 21 questions · 1 written answer
Basics
First Name, Last Name, Email, Phone, Resume/CV
Short answers (4)
- What is Your notice period?
- LinkedIn Profile optional
- Capco employee email address
- If other, please specify? optional
Pick from a list (16)
- Were you referred to this role by a current Capco Employee? If yes, please confirm the employee’s Capco email address.
- Reasonable Adjustments
- How did you hear about this role?
- What is your current location?
- Are you authorized to work in the country in which you’re applying?
- Capco Job Candidate Privacy Notice Acknowledgement
- How many years of professional experience do you have in Data Analysis?
- How would you rate your hands-on SQL skills, including complex joins, CTEs, window functions, and data reconciliation?
- How much hands-on professional experience do you have with Python for data analysis and transformation?
- Which of the following technologies have you used professionally?
- Have you used PySpark to process or transform large datasets in a production environment?
- Have you worked on data quality checks, reconciliation, or investigating discrepancies between datasets?
- Have you worked directly with business stakeholders to gather requirements and translate them into data transformation logic or technical specifications?
- Do you have experience working in banking, financial services, or regulatory reporting?
- Do you have experience with ESG reporting frameworks such as EU Taxonomy, EBA Pillar 3 ESG, or SREP?
- Are you comfortable working under a B2B contract in a hybrid model, with attendance at the Kraków office (6x per month) as agreed based on project needs?
Written answers (1)
- What is your rate?
