What you can expect You take on the functional and disciplinary responsibility for all FTEs in the Sales Data Hub within the federated data setup, including Data Engineers, Data Scientists, Data Governance roles and Product Owners Data.You define, design, develop, and operate cloud‑based data products for the Sales, Marketing, and Customer Service business units.You are responsible for the methodological integration of data assets and data products.You manage the Sales Data Hub operationally and further develop it as a specialized unit for data‑driven solutions in Sales, Marketing, and Customer Service.You are responsible for the further development and ongoing maintenance of all sales‑related models based on feedback and requirements from the sales organization.You lead projects related to planning, expanding, and organizing new and existing products in collaboration with the relevant business units and external partners.You assume technical responsibility for data products developed by or for the Sales, Marketing, and Customer Service areas within the Data Intelligence & Analytics team.You drive the continuous expansion, professionalization, and organizational development of the Sales Data Hub within the existing governance and organizational framework.
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.
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.
DKV is the full‑service provider in the field of eMobility, offering tailor‑made solutions for electric vehicles: from charging infrastructure to planning and design, from consultancy to installation and electricity products. As a Customer Support Representative, you are the coordinator and take ownership of our service delivery.
In this position you will work with applications engineers, product engineers and account managers to design and offer Leybold service and solutions that helps clients supercharge their process efficiencies. This position acts as the service sales liaison between the Leybold factory and the client with the intent to teach companies how to maximize the life cycle of their equipment through means of the VTS Service Ladder.
You are responsible for the conceptual, logical, and structural integrity of our Core Data Model as well as the Gold Layer across Azure, Snowflake, and dbt.You ensure that fragmented data sources are transformed into consistent, reusable, and decision‑relevant data products, actively preventing the platform from drifting into team‑specific, incompatible models.You define and maintain central business objects, canonical dimensions, shared metrics, and facts, ensuring that the Core Data Model serves as a stable, business‑oriented foundation across all domains.You develop modeling standards, naming conventions, layering concepts (Staging → Intermediate → Gold), reuse patterns, and dbt design guidelines, and you ensure their consistent implementation across all teams.You safeguard the semantic consistency of the entire data model, resolve domain conflicts, ensure that identical business terms are modeled only once, and review changes affecting core layers.You act as the technical design authority for model changes in Snowflake/dbt, balancing local requirements with long‑term model coherence, and ensuring that all models remain performant, scalable, maintainable, and of high quality.