Senior Data Engineer

pAs a bSenior Data Engineer /b you will join a newly forming AI Hub with the mission to build the data and application foundation behind scalable AI tools and platforms. Your work will directly shape how enterprise data is accessed, transformed, retrieved, and used to power AI solutions that improve the way our business operates and the way our clients experience our services. This is not a role focused on building isolated data pipelines or supporting one-off prototypes. We are building AI capabilities that need to be secure, reusable, scalable, and ready for enterprise adoption. That means the data foundation behind them must be strong, well-designed, and practical enough to support real-world use. We are looking for a builder who understands that great AI depends on great data engineering, robust software design, secure access patterns, and reliable retrieval foundations. Someone who thinks beyond the task, challenges existing patterns, and brings bold but practical ideas to the table. You should be comfortable operating in an evolving environment, actively using AI in your own work, and helping us shape reusable data capabilities that will support the future of AI across the company. /pbrScroll naar beneden voor de volledige details van de vacature, inclusief de vereiste ervaring en de bijbehorende taken.brWho we arebrpflatexDEGIRO SE operates the leading and fastest growing online brokerage platform in Europe. Based on modern, in-house state‑of‑the‑art technology, customers of the flatex and DEGIRO brands are offered a wide range of independent products with execution on top TIER 1 exchanges. The technological edge, high efficiency and strong economies of scale enable us to continuously improve our service offering for clients and to set leading standards in terms of product, price and platform quality. /pbrThis is what you’ll be doingbrullibr/liliBuild secure ingestion, transformation, and retrieval pipelines for enterprise data.br/liliDevelop scalable APIs and application components that support AI services and RAG-based solutions.br/liliDesign and maintain data access patterns that are secure, governed, and aligned with compliance requirements.br/liliWork with structured and unstructured data sources to support retrieval, vector search, and AI application needs.br/liliCreate reusable data components, internal SDK patterns, and technical building blocks for future AI workloads.br/liliEnable governed access to enterprise data sources in line with security, privacy, and internal control standards.br/liliIntegrate AI services with existing CI/CD, observability, monitoring, and IT control processes.br/liliCollaborate with AI Engineers, MLOps Engineers, architects, security, IT operations, and business stakeholders.br/liliMaintain high standards for code quality, automation, performance, and operational resilience.br/liliProactively identify ways to improve data availability, retrieval quality, and reusability across AI use cases.br/liliActively use AI in your own engineering work to improve productivity, automation, testing, documentation, and delivery speed.br/li /ulbrYou’ll bring us these skillsbrpWe are looking for an experienced engineer who can combine strong data engineering skills with software engineering discipline and a pragmatic AI mindset. You should be comfortable building foundations that others can reuse, extend, and scale. /pbrullibr/lili5 to 8 years of experience in software engineering, data engineering, platform engineering, or a similar technical role.br/liliStrong hands‑on experience with Python and SQL.br/liliExperience building and delivering services in production environments.br/liliStrong understanding of APIs, integration patterns, and secure enterprise architecture.br/liliFamiliarity with vector databases, search, retrieval patterns, and RAG‑related architectures.br/liliExperience with CI/CD, containers, observability tooling, and modern engineering practices.br/liliGood understanding of data governance, access control, security, privacy, and compliance requirements.br/liliAbility to build reusable components, internal libraries, SDK patterns, or scalable technical foundations.br/liliExperience with RAG-based applications or similar AI architectures would be considered an advantage.br/liliFamiliarity with infrastructure automation and API security would be a plus.br/liliBackground in financial services, fintech, banking, or another regulated environment would be beneficial.br/li /ulbrMost importantlybrpYou bring a proactive and value‑oriented mindset. You do not only build pipelines because they were requested. xgiwjmb You think about what data foundations AI teams will need next, how to make them reusable, and how to balance speed, quality, and governance in a fast‑moving environment. /pbrThis is what we offer youbrullibr/liliPromise of a good work‑life balancebr/lili30 days paid leavebr/liliAn enthusiastic and fun team to work withbr/liliPersonal and professional development with access to relevant coursesbr/liliTransport allowance or related benefits like a leased electric bikebr/liliPension planbr/liliA challenging job in an international and fast‑growing companybr/liliA competitive salarybr/liliA lot of freedom executing your role and a chance to shape your own careerbr/liliThe opportunity to participate in a new, enthusiastic team of likeminded professionalsbr/liliFreedom to work flexiblybr/liliCompany laptop and options to make your home workspace comfortable, such as a chair, screen and headphonesbr/liliGym membership optionsbr/li /ulbr