Senior Data Analyst — Financial ML & ETL Pipelines

Capco; Kraków; Hybrid; PLN 150,000 - 210,000; Full time

Benefits offered by this job

B2B contract

Job summary

Capco Poland is hiring an experienced Data Analyst to support ML model development in a global financial services context. You will source, transform, and prepare large datasets and build robust ETL processes, partnering with data scientists, model developers, and business stakeholders.

Ideal candidates have 4–5+ years in data analysis, strong SQL/Python, and comfort with large-scale data environments, with fluent English communication.

Qualifications

• 4–5+ years of experience as a Data Analyst.
• Strong proficiency in SQL and Python.
• Experience with NumPy, SciPy and PySpark.
• Data wrangling, data transformation, and ETL processes.
• Banking or financial services domain knowledge desirable.
• Bachelor's degree in CS/Engineering/Math or related field.
• Excellent communication and stakeholder management skills.
• Fluent English, written and spoken.

Responsibilities

• Source, transform, analyze, and prepare large-scale datasets.
• Design, develop, and optimize ETL pipelines.
• Aggregate data from multiple internal and external sources.
• Collaborate with model developers, data scientists, and business stakeholders.
• Identify data quality issues and implement solutions to improve data accuracy and accessibility.
• Contribute to continuous improvement of data management and analytics processes.

Skills

SQL

Python

NumPy

SciPy

PySpark

Data wrangling

ETL processes

Analytical thinking

Fluent English

Education

Bachelor's degree (CS/Engineering/Math)

Tools

PySpark

Job description

Capco Poland is hiring an experienced Data Analyst to support ML model development in a global financial services context. You will source, transform, and prepare large datasets and build robust ETL processes, partnering with data scientists, model developers, and business stakeholders.

Ideal candidates have 4–5+ years in data analysis, strong SQL/Python, and comfort with large-scale data environments, with fluent English communication.