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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** flatexDEGIRO SE - **Location:** Amsterdam, Netherlands - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Component-Based Software Engineering, Software Quality, Continuous Integration, Information Engineering, Data Governance, DevOps, Information Technology Operations, Python (Programming Language), Search Technologies, Software Engineering, SQL Databases, Datadog, System Availability, Software Security, AI Platforms, Infrastructure Automation Frameworks, Data Management, Machine Learning Operations, Data Pipelines - **Published:** May 21, 2026 - **Apply:** https://nl.indeed.com/viewjob?jk=de30e6dbfd68405d ## About the Role Do you have experience in Security?, We 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. You'll bring us these skills: * 5 to 8 years of experience in software engineering, data engineering, platform engineering, or a similar technical role. * Strong hands-on experience with Python and SQL. * Experience building and delivering services in production environments. * Strong understanding of APIs, integration patterns, and secure enterprise architecture. * Familiarity with vector databases, search, retrieval patterns, and RAG-related architectures. * Experience with CI/CD, containers, observability tooling, and modern engineering practices. * Good understanding of data governance, access control, security, privacy, and compliance requirements. * Ability to build reusable components, internal libraries, SDK patterns, or scalable technical foundations. * Experience with RAG-based applications or similar AI architectures would be considered an advantage. * Familiarity with infrastructure automation and API security would be a plus. * Background in financial services, fintech, banking, or another regulated environment would be beneficial. Most importantly, you bring a proactive and value-oriented mindset. You do not only build pipelines because they were requested. 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. ## Description As a Senior Data Engineer 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. This is what you'll be doing * Build secure ingestion, transformation, and retrieval pipelines for enterprise data. * Develop scalable APIs and application components that support AI services and RAG-based solutions. * Design and maintain data access patterns that are secure, governed, and aligned with compliance requirements. * Work with structured and unstructured data sources to support retrieval, vector search, and AI application needs. * Create reusable data components, internal SDK patterns, and technical building blocks for future AI workloads. * Enable governed access to enterprise data sources in line with security, privacy, and internal control standards. * Integrate AI services with existing CI/CD, observability, monitoring, and IT control processes. * Collaborate with AI Engineers, MLOps Engineers, architects, security, IT operations, and business stakeholders. * Maintain high standards for code quality, automation, performance, and operational resilience. * Proactively identify ways to improve data availability, retrieval quality, and reusability across AI use cases. * Actively use AI in your own engineering work to improve productivity, automation, testing, documentation, and delivery speed. * You'll bring us these skills ## Related Videos - [This App Reached 10,000 Users in One Week. 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