Data Engineer (AI) banking

emagine Polska; Województwo pomorskie; Hybrid; PLN 262,000 - 317,000; Full time

Job summary

emagine Polska is seeking a Data Engineer to design, build, and maintain scalable data pipelines for corporate lending operations. You will leverage Python, PySpark, and SQL to transform data into reliable analytics and drive insights for stakeholders.

The role covers data modeling, quality checks, data lineage, and managing the data warehouse and data lake. You will collaborate with product managers in an agile environment and ensure regulatory compliance.

Qualifications

• Proficiency in Python, PySpark and SQL.
• Experience with ETL/ELT pipeline development.
• Cloud data warehouse/lake experience.
• Experience with AWS and services (e.g. Sagemaker AI, Event Bridge).
• Data modeling, quality, and lineage expertise.
• Experience with ML model development and deployment.

Responsibilities

• Design, build, and maintain scalable data pipelines for internal banking systems and external data providers.
• Develop and optimize data models for corporate lending domains, including loan origination and repayment history.
• Implement data quality checks, validation rules, and data lineage.
• Manage and evolve the data warehouse and lake for analytics and reporting.
• Ensure compliance with regulatory and data governance requirements.
• Collaborate with product managers and domain experts in an agile setting.
• Document data pipelines, models, and key design decisions.

Skills

Python

PySpark

SQL

ETL/ELT

Cloud data warehouse

AWS

Sagemaker AI

EventBridge

Data modeling

Data quality & lineage

ML model development

Tools

AWS

Sagemaker AI

EventBridge

Job description

General info:

Rate: 190 PLN net + vat/ hour
Type of contract: B2B, long term cooperation
Model of work: hybrid, 1 day per week work from office (Gdańsk/ Warsaw/ Łódź)

Introduction & Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines, specifically focused on supporting corporate lending operations. The ideal candidate must be proficient in Python, PySpark, and SQL and possess experience with ETL/ELT pipeline development. This role requires a strong analytical mindset, able to transform data insights into actionable recommendations for stakeholders.

Main Responsibilities

• Design, build, and maintain scalable data pipelines for internal banking systems and external data providers.
• Develop and optimize data models for corporate lending domains, including loan origination and repayment history.
• Implement data quality checks, validation rules, and data lineage.
• Manage and evolve the data warehouse and lake for analytics and reporting.
• Ensure compliance with regulatory and data governance requirements.
• Collaborate with product managers and domain experts in an agile setting.
• Document data pipelines, models, and key design decisions.

Key Requirements

• Proficiency in Python, PySpark and SQL
• Experience with ETL/ELT pipeline development
• Cloud data warehouse/lake experience
• Experience with AWS and services (e.g. Sagemaker AI, Event Bridge)
• Data modeling, quality, and lineage expertise
• Experience with ML model development and deployment

Nice to Have

• Corporate lending or financial services background
• Knowledge of credit decision processes
• Experience with LLM/GenAI integration
• Agentic AI implementations
• Understanding of model explainability