Senior Data Engineer (Snowflake)

We are looking for a Senior Data Engineer to join a growing team in Kraków. In this role, you will help build and evolve the data platform behind a mission-critical, AI-powered SaaS product used by customers and internal teams to support high-value business decisions.

You will work hands-on with Snowflake, modern ELT/ETL tooling, SQL, data modelling, data quality frameworks, and AI-assisted development tools such as Claude and Cursor. The role combines data engineering, analytics engineering, platform ownership, and close collaboration with product, engineering, and finance stakeholders.

What you will work onBuild and maintain reliable ELT/ETL pipelines that move data from transactional systems, microservices, event streams, and external sources into Snowflake.

Design clean, performant, and scalable data models for reporting, analytics, and customer-facing insights.

Contribute to the architecture of the end-to-end data platform, from ingestion and transformation to serving and analytics.

Apply modern data modelling practices, with a focus on modular, tested, and well-documented models.

Use AI development tools such as Claude and Cursor to accelerate pipeline development, query optimisation, documentation, and quality improvements.

Implement data quality checks, automated testing, monitoring, and observability into data pipelines from the start.

Support code reviews, documentation, and knowledge sharing around Snowflake, data modelling, performance optimisation, and data platform best practices.

Work closely with Software Engineers, Product Managers, Finance stakeholders, and analytics teams to translate data needs into reliable data products.

What we are looking forStrong hands-on experience with Snowflake, including data modelling, performance tuning, cost optimisation, and security/governance features.

Proven experience building production-grade ELT/ETL pipelines using tools such as dbt, Apache Airflow, Azure Data Factory, or similar.

Expert-level SQL skills.

Working knowledge of at least one general-purpose programming language, preferably Python, for automation and data processing.

Practical experience using AI-assisted development tools such as Claude or Cursor to improve speed, quality, and documentation.

Strong data quality mindset, including testing, monitoring, alerting, and observability.

Ability to take ownership of well-scoped initiatives from unclear requirements to reliable, adopted data products.

Strong communication skills and ability to explain technical data topics to business stakeholders.

Nice to have

Experience with Power BI, including semantic models, DAX, Power Query, report design, row-level security, incremental refresh, and Power BI Service.

Experience in finance, accounting, fintech, or another regulated environment.

Familiarity with Microsoft Fabric, including data mirroring from Azure-hosted sources.

Experience with cloud-native data architectures in Azure or AWS, such as Azure Synapse, Azure Data Lake, AWS Glue, or S3-based data lake patterns.

Experience with streaming or event-driven ingestion using Kafka, Azure Event Hubs, or similar technologies.

Understanding of Responsible AI principles and data infrastructure supporting auditable AI/ML pipelines.

Interest in modern data stack trends, open-source tooling, or emerging analytics engineering practices.