As part of our team, you will take on the following responsibilities: You develop and maintain cloud‑based data pipelines and data products specifically for the Finance domain, built on our Snowflake database.You integrate financial and transactional data from various sources into our central Data Platform, optimize ETL processes, and ensure high data quality.You design and build new DataFlows and DataSets for Finance use cases and create as well as manage the corresponding Power BI reports.You collaborate closely with Finance Product Owners, Data Scientists, and Business Units to deliver meaningful analytical data products.You take ownership of data governance for all Finance data products and actively drive their further development.You support the modernization of our Finance data architecture and contribute to the migration towards cloud‑ and big‑data‑based technologies. What makes you stand out You hold a degree in Computer Science, Business Informatics, or a comparable qualification.You have strong expertise in SQL databases, including data modeling, table design, and data querying — ideally with experience in Snowflake.You bring experience in developing and integrating data products and are familiar with Azure Data Factory, Python, and modern cloud technologies (preferably Azure).You have hands‑on experience creating meaningful Power BI reports; knowledge of CI/CD or container technologies (e.g., Docker, Kubernetes) is a plus.You work analytically, communicate effectively, collaborate well in teams, and demonstrate a strong hands‑on mentality.You are fluent in English and have very good German skills; you also have a passion for financial databases and enjoy exploring new topics.
As part of our team, you will take on the following responsibilities: You are the driving force that transforms innovative AI/ML concepts from the lab environment into robust, scalable products — ensuring prototypes evolve into stable, production‑ready systems.You operationalize the entire ML lifecycle, developing automated CI/CD pipelines, taking ownership of deploying models into production, and continuously expanding our resilient MLOps infrastructure.You implement algorithms and complex feature transformations efficiently within production systems, optimizing them for latency, throughput, and maximum stability.You build scalable data pipelines and feature stores that ensure reliable, consistent data supply for both training and serving — online and offline.You establish professional monitoring mechanisms such as drift detection, automated retraining, and validation processes to guarantee long‑term model quality in live operations.You collaborate closely with Data Scientists, MLOps teams, and IT Infrastructure teams, ensuring that all production‑grade AI/ML solutions follow software engineering best practices and comply with security, privacy, and regulatory requirements. What makes you stand out You hold a master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.You have at least 3 years of professional experience in ML Engineering or MLOps, with a proven track record of building, deploying, and operating tailored AI/ML solutions in production.You bring deep expertise in Python and SQL, hands‑on experience with cloud platforms (ideally Azure), and familiarity with data warehouses such as Snowflake; foundational knowledge of Infrastructure‑as‑Code tools like Terraform is a plus.You are proficient with CI/CD tools (e.g., Azure DevOps), containerization technologies (Docker/Kubernetes), and apply modern software design patterns confidently.You thrive in a dynamic, agile, and innovative environment, working effectively both independently and as part of a team.You possess excellent English communication skills, both written and spoken; German language skills are considered a plus.