Senior Data Engineer

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.

Who we are

flatexDEGIRO 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.

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

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.

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.

This is what we offer you

Promise of a good work‑life balance

30 days paid leave

An enthusiastic and fun team to work with

Personal and professional development with access to relevant courses

Transport allowance or related benefits like a leased electric bike

Pension plan

A challenging job in an international and fast‑growing company

A competitive salary

A lot of freedom executing your role and a chance to shape your own career

The opportunity to participate in a new, enthusiastic team of likeminded professionals

Freedom to work flexibly

Company laptop and options to make your home workspace comfortable, such as a chair, screen and headphones

Gym membership options

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