Senior Data Engineer; Python & AI

Your mission

We in Etops are a very intensely cooperating team where every single person takes ownership and contributes to our joint success. Everyone matters – individually and as a team.

Our integrated ecosystem combines portfolio management, CRM, reporting, compliance, data integration, outsourcing and intelligent automation into one scalable platform. By transforming data into actionable insights, we enable financial professionals to deliver exceptional client experiences, make better decisions and grow their businesses sustainably.

As our platform continues to evolve, data is at the heart of everything we build. That's why we're looking for a Senior Data Engineer who wants to shape the next generation of data-driven products, AI-powered applications and scalable platform services. You'll work with modern technologies, take ownership from idea to production and have a direct impact on the products used by thousands of financial professionals across Europe.

In this position you will be responsible for:

• Develop and enhance data-driven applications. You work on our Python- and Streamlit-based applications for internal and external users. You implement new features, improve existing functionality and write clean, maintainable code that delivers real business value.
• Work with data every day. You analyse complex datasets, write efficient SQL queries and transform data into meaningful insights that support business decisions and customer-facing solutions.
• Maintain and optimise data pipelines. You work with our Airflow pipelines to ensure reliable data processing, high data quality and strong performance. You continuously improve existing pipelines and integrate new data sources where needed.
• Apply AI where it adds value. You contribute to Machine Learning models and LLM-powered applications, helping bring technologies such as RAG, vector search and Agentic AI into practical, production-ready use cases.
• Support analytics and BI. You collaborate closely with our BI team, optimise SQL queries, improve data models and troubleshoot performance issues to ensure reliable analytical solutions.
• Write production-ready software. You turn ideas and prototypes into robust, tested and maintainable applications using modern software engineering practices.
• Stay curious. Technology evolves quickly—and so do you. You enjoy learning, exploring new tools and experimenting with emerging AI and data technologies to continuously improve your work.
• Collaborate and share knowledge. You work closely with Product, BI, Software Engineering and business stakeholders. Through code reviews, technical discussions and knowledge sharing, you actively contribute to the success of the team.

We are looking for:

• 5+ years of professional experience developing production-grade applications with Python.
• Strong experience building and maintaining data-driven applications, ideally with Streamlit.
• Excellent SQL skills and a deep understanding of relational databases (e.g. PostgreSQL, Oracle), including query optimisation, data modelling and performance tuning.
• Hands‑on experience working with Airflow or similar orchestration frameworks.
• Practical experience with Machine Learning, LLMs or Generative AI, including technologies such as RAG, embeddings or vector search.
• Experience with Elasticsearch is a plus.
• Solid knowledge of Git/Git Hub, code reviews and modern CI/CD workflows.
• Experience with Docker and modern development environments.
• A passion for coding and solving complex analytical problems.
• A curious mindset with a genuine interest in learning new technologies and continuously improving your skills.
• Strong analytical thinking and the ability to translate complex business requirements into elegant technical solutions.
• A collaborative attitude, excellent communication skills and fluency in German and English.

• HTML, CSS and JavaScript to extend Streamlit applications.
• Experience with Google Cloud Platform and/or Microsoft Azure.
• Experience with dbt and modern data transformation practices.
• Experience with pandas, Polars, PySpark and pytest.
• Experience with Agentic AI, vector databases (e.g.…