Data Engineer

• Banking

• B2B up to 170zł/h

• Hybrid work in Gdańsk - 3 days per week in the office

• Long-term

Main Responsibilities

As a Database Engineer, you will be responsible for:

• Designing, implementing, maintaining, and optimizing Snowpark and DBT workflows

• Building and improving scalable data transformation pipelines within a modern data warehouse environment

• Developing and optimizing complex SQL queries, data models, and database processes

• Supporting the design and implementation of CI/CD pipelines for data engineering workflows

• Building and improving automated testing frameworks to ensure data quality and reliability

• Monitoring recurring and monthly production jobs, identifying failures, performance issues, or data inconsistencies

• Troubleshooting data pipeline and database-related issues and implementing long-term improvements

• Optimizing existing workflows with a focus on performance, stability, maintainability, and automation

• Supporting the development and implementation of AI agents and exploring opportunities to use AI to automate or improve data-related processes

• Collaborating with business stakeholders to understand requirements and translate them into technical solutions

• Working closely with engineering, data, and business teams across the organization

• Documenting implemented solutions, workflows, and technical processes

Key Requirements

• SQL – strong practical knowledge, including writing and optimizing complex queries

• DBT – hands-on experience designing and maintaining data transformation workflows

• Data Warehousing – good understanding of data warehouse architecture, data modeling, transformation, and data processing concepts

• Snowpark / Snowflake ecosystem – experience working with Snowpark or similar modern cloud data platforms

• CI/CD – experience implementing or maintaining automated deployment pipelines

• Test automation – understanding of automated testing approaches within data engineering environments

• AI agent development / creation – practical exposure to building AI-powered agents or implementing agent-based automation

• Experience with monitoring, troubleshooting, and optimizing scheduled data processing jobs

• Strong communication skills and ability to cooperate with both technical and non-technical stakeholders

• Professional working proficiency in English

Nice to Have

• Previous experience within banking or financial services

• Knowledge of Credit Risk processes, data, or systems

• Experience working with large-scale enterprise data environments

• Understanding of data governance, data quality, and regulatory requirements within financial institutions