Data Engineer – Data & AI

This role sits within a dynamic, global IT team and focuses on turning complex enterprise data into trusted, actionable insights that support smarter decision-making across the organisation. It bridges business, data science, and IT, designing and operating the data products, integration services, and platforms that empower business analysts, data scientists, and AI engineers worldwide. The position operates in a highly integrated, global environment shaping the next generation of data engineering and AI-powered analytics.

• Collaborate closely with data scientists, business analysts, and solution and analytics architects to shape innovative data solutions and products.
• Drive the implementation, testing, and support of modern data pipelines using contemporary engineering practices.
• Develop dynamic ELT pipelines and efficient approaches to data ingestion, preparation, integration, and operationalisation using modern analytics engineering platforms and technologies such as Snowflake, Azure Data Factory, DBT, and Dagster
• While contributing to strong data governance and compliance standards.
• Create data solutions that are scalable, secure, reusable, and easy to maintain, ensuring alignment with enterprise architecture standards and best practices.
• Apply AI in ways that support business objectives while ensuring adherence to security, privacy, governance, and responsible AI principles.
• Work closely with AI engineers to design and productionise the data foundations required for AI-powered analytics, ensuring AI systems have access to high-quality data, features, embeddings, metadata, and evaluation datasets.
• Establish and continuously enhance governance frameworks and processes with Data Science teams, Data Cloud Architects, and business stakeholders to promote the responsible and effective use of data and technology.
• Build strong relationships across IT, Data, Sales, Operations, Marketing, Finance, and other business functions to foster alignment and collaboration.
• Partner with DevOps, MLOps, and Analytics Engineers to maximise data availability, reliability, and accuracy and to continuously improve data quality.
• Translate business requirements and use cases into effective data-driven solutions and drive continuous process improvement initiatives to enhance efficiency and service delivery.
• Create clear documentation and engaging presentations that facilitate knowledge sharing, alignment, and effective communication across teams.

• University degree in IT or business administration with a focus on computer science, data science, or data engineering.
• Fluency in English.
• At least three years of experience with analytics tools such as Azure Data Factory, Snowflake, Databricks, BigQuery, Dagster, or DBT.
• Experience with SQL and Python.
• Architectural understanding of databases and ETL/ELT pipelines.
• Demonstrated enterprise mindset, with the ability to align data-engineering solutions with broader business strategy, architecture, governance, security, compliance, and operational requirements.
• Experience using AI coding assistants or AI-enabled data-platform tools in a professional environment.
• Familiarity with data science and data lake platforms on modern hyperscalers such as Azure or AWS.
• Enthusiasm for both engineering tasks and the implementation of business requirements.

• German language skills.
• Knowledge of SAP (BW, HANA, SAC) and analytics front-end tools.