Data Engineer

We're looking for a Data Engineer who's not only technically strong but also thrives in ambiguity, can work through legacy constraints, and is passionate about making data reliable, timely, and actionable.

As a Data Engineer, you'll be responsible for designing, maintaining, and evolving our modern data stack - including Snowflake, Airbyte, dbt, and orchestration tools such as Mage and N8N. You'll work closely with data scientists, analysts, and business stakeholders to improve how we collect, model, and serve data across the organization.

This role is ideal for someone who enjoys building reliable systems, working with cross-functional teams, and ensuring data is timely, accurate, accessible, and actionable.

• Design and maintain scalable, reliable data pipelines for batch and real-time ingestion using Airbyte, REST APIs, SFTP, and other sources.

• Develop, maintain, and optimize data models in SQL & NoSQL databases, Snowflake using dbt, with a focus on developing robust data models (eg. Dimensional modeling, Data Vault, OBT strategies).

• Writing clear documentation, implementing tests to ensure data quality, and version control of code.

• Build and manage data orchestration workflows with Jenkins, Mage and N8N to ensure reliable automation and timely data availability.

• Monitor and manage data quality, integrity, and performance.

• Administer and optimize Snowflake including IAM management, cost optimization and ensuring data integrity and security.

• Develop and actively contribute to the architecture of the future-state data platform.

• Work with stakeholders to define data requirements, and ensure models and pipelines meet business and compliance needs.

• A chance to help shape the future of data in a company where your work will have immediate impact.

• Real-world technical challenges - not everything is perfect, but you'll have the opportunity to fix and improve things.

• Your pipelines and models will directly support critical workflows such as regulatory reporting, financial reconciliation, and machine learning operations.

• Be part of a collaborative, impact-driven team of experienced and supportive professionals.

• Hybrid work model (we have nice offices in Prague - Karlín).

• Home office reimbursement.

• Informal and pleasant atmosphere - we all know and respect each other and we also have a pack of dogs.

• Promoting a healthy lifestyle - we do offer flexible working hours, drinking and fruit daily in the office, team events, up to 34 days of vacation or additional 5 days paid leave for parents after child birth, etc.

5 years in Data Engineering or a similar role in a modern data environment (not necessarily perfect, but moving in the right direction).

Expertise in:

• SQL (PostgreSQL, MySQL, Maria DB, complex queries, performance tuning)

• Python for data transformation, automation, and integration workflows

• dbt (including testing, macros, packages)

• NoSQL databases (MongoDB, DynamoDB, Cassandra, or similar) for flexible, high-volume data storage.

• Snowflake (or similar cloud data warehouse)

• Airbyte or similar ingestion tools (Fivetran, Stitch)

• Orchestration tools like Mage, N8N, Airflow, or similar

• Experience working with cloud platforms (eg. GCP, AWS or similar)

• Familiarity with data governance, version control (git), CI/CD, and documentation

• Strong understanding of data architecture principles and scalable design patterns

• Experience in regulated environment (e.g., fintech, banking)

• Exposure to financial data (PnL, credit, provisioning, etc.)

• Understanding of data security, IAM, and compliance requirements in cloud environments