What will keep you challenged?

• Design, build, and optimize scalable data pipelines and storage solutions that ensure efficient, secure, and reliable data processing from source systems to our data warehouse
• Develop and manage ETL/ELT workflows to integrate data from multiple sources, ensuring seamless ingestion, transformation, and availability
• Implement and enforce data quality, validation, and monitoring processes to guarantee accuracy and integrity for analytics and operational use cases
• Ensure data security and compliance by applying best practices and industry standards for handling sensitive information
• Collaborate with analysts, product managers, and engineers to understand data needs and deliver solutions that unlock new insights
• Continuously evaluate and integrate new technologies to improve scalability, performance, and future-proof LIQID’s data infrastructure
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What you bring

• Over 5 years of professional experience in data engineering, data architecture, or a similar data related role
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field
• Strong proficiency in SQL, Python and ETL/ELT frameworks, with experience in data modelling, warehousing, and database management (e.g., BigQuery, Snowflake, PostgreSQL)
• Experience with cloud data platforms (e.g., AWS, Google Cloud) and modern data pipeline tools (e.g., Airflow, dbt)
• Solid understanding of data modelling principles to meet data governance, security, and compliance best practices and ensure safe and scalable data operations
• FinTech experience is a plus, but a strong interest in financial services and data-driven decision-making is essential
• Experience using AI coding tools (Copilot, Cursor, Claude) to speed up development and integrating them into standard workflows (code review, CI/CD), with the judgment to verify output, not just ship it.
• Experience with data quality testing frameworks or rules-as-code approaches (e.g. dbt tests, Great Expectations) to catch issues before they hit production.
• Experience with streaming/near-real-time pipelines (Kafka, Kinesis, or similar) is a plus.
• Fluent in English, both written and spoken; German is a plus