Data Transformation Manager

Quick Facts

• Role: Data Transformation Manager

Description

You will shape Data Operations by combining technology, automation, and AI to turn complex business needs into smart, scalable solutions. You will take initiatives from concept through implementation and help create more efficient ways of working with data.

Responsibilities

• Identify, design, build, and implement automation, application development, and AI solutions across Data Operations.
• Own the automation and application development portfolio end-to-end: opportunity assessment, business case creation, architecture, development, deployment, and value realization.
• Translate business requirements into technical specifications, solution architecture, user stories, and scalable software products; bridge Data Operations, IT, data platform teams, and external partners.
• Develop, test, and maintain custom applications, automation frameworks, APIs, data pipelines, Copilot agents, and AI-powered solutions using software engineering best practices (CI/CD, version control, testing, monitoring).
• Build reporting and analytics to measure automation adoption, service performance, operational efficiency, and business impact; ensure solutions are secure, scalable, well-documented, and maintainable.

Requirements

• Several years of experience in software engineering, automation engineering, application development, data engineering, or solution architecture in financial services/banking/asset management or other regulated industries.
• Hands-on development experience in Python, SQL, Databricks, APIs, Microsoft Power Platform, and Power BI; strong understanding of software architecture, databases, data modeling, and data quality.
• Experience building enterprise applications, automation solutions, system integrations, and AI/LLM capabilities including Copilot, intelligent agents, workflow orchestration, and RAG solutions.
• Delivery mindset in Agile environments, translating business challenges into scalable technical solutions; experience with Jira, Confluence, Git, and CI/CD practices; familiarity with OpenShift/Kubernetes.
• Strong stakeholder management and communication skills; ability to explain complex technical concepts to non-technical audiences. Financial market data experience and German language skills are advantageous.

Benefits

• Hybrid model: up to 40% working from home
• Private medical care and life insurance
• Meal, transportation, and electricity allowance
• Sport card
• Cinema tickets and Benefit System points
• Up to 20 days working abroad per year (Day for U)
• Access to technical and language learning platforms