Senior Data Engineer

Your Role We are looking for a Senior Data Engineer (f/m/d) at LIQID, who will play a pivotal role in building and scaling data infrastructure that powers decision-making. You will design scalable, high-performance data pipelines, ensure data integrity, and drive efficient data processing across the organization. Working closely with our Head of Data, Analytics Engineers, and cross-functional teams, you will develop robust data architectures, enhance data security, and implement best practices that empower data-driven decision-making at scale. This is not a role where you preserve what already exists. It is a role where you build what comes next. As LIQID scales beyond €4 billion in assets under management, the demands on our data infrastructure are growing fast. You will have real ownership over how we meet that challenge, with the autonomy to propose solutions and the backing to ship them. 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 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 (K