Data Engineer

This position is within the banking industry, focusing on long-term data engineering work involving modern data warehouse environments.

• Strong practical knowledge of SQL, including writing and optimizing complex queries
• Hands-on experience with DBT designing and maintaining data transformation workflows
• Good understanding of Data Warehousing architecture, modeling, transformation, and processing
• Experience with Snowpark / Snowflake ecosystem or similar modern cloud data platforms
• Experience implementing or maintaining automated CI/CD deployment pipelines
• Understanding of test automation approaches within data engineering environments
• Practical exposure to AI agent development / creation or agent-based automation
• Experience monitoring, troubleshooting, and optimizing scheduled data processing jobs
• Strong communication skills for cooperation 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

• 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 focusing 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