Senior AI Data Engineer – Financial Data Infrastructure

As a Senior AI Data Engineer – Financial Data Infrastructure, you will build reliable, scalable, and secure data systems supporting next-generation AI applications in financial services. Your work will enable innovative solutions and data-driven insights.

Your main responsibilities

• Design and implement scalable data pipelines and ETL/ELT processes.
• Build and maintain data warehouses and data lakes for large-scale financial datasets.
• Ensure data quality, consistency, and compliance with industry regulations.
• Transform and prepare data for machine learning models and predictive analytics.
• Collaborate with AI Engineers and Data Scientists to optimize training and inference pipelines.
• Work with real-time data streaming platforms such as Kafka or Spark Streaming.
• Manage SQL and NoSQL databases, ensuring high availability and performance.
• Monitor, troubleshoot, and optimize data flows and infrastructure performance.
• Contribute to cloud-based data architecture and infrastructure management.
• Document data workflows, processes, and best practices.

You’re ideal for this role if you have

• Minimum 3 years of experience as a Data Engineer, AI Data Engineer, or in a similar role.
• Proficiency in ETL/ELT processes and data pipeline development.
• Strong knowledge of big data technologies such as Spark, Kafka, or Hadoop.
• Experience with SQL and NoSQL databases.
• Hands-on experience with AWS, GCP, or Azure for data engineering solutions.
• Understanding of machine learning workflows and data preparation for AI models.
• Ability to work with both batch and real-time data processing.
• Strong problem-solving skills and attention to detail.
• Fluent English and Polish, with excellent communication skills.
• Existing legal right to work in the European Union.

Experience in the finance or banking industry is a strong advantage.

Apply with a CV in English or Polish and a statement confirming consent to the processing and storage of personal data.