Data Engineering Lead - Data & AI Tools (m/f/d)

At Statista , we’re all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions.

Founded in Hamburg in 2007, we have quickly grown into a global company with offices in major cities such as London, New York, Berlin and Tokyo. And we still have a lot of plans. Our constant growth does not only prove our success, but also keeps creating new development and career opportunities for our employees.

We value and celebrate our diverse culture. You are welcome here for who you are, no matter where you come from, what you look like, or whether you prefer bar graphs to pie charts. Your story matters – keep writing it as part of our team.

Are you ready to join us?

• Lead and mentor a team of Data and AI engineers, setting objectives, reviewing code, and fostering professional growth.
• Drive the end-to-end development of advanced Data and AI-powered solutions, including automation frameworks and agentic workflows, to enhance data research, complex forecasting, and decision-making
• Design, deploy, and maintain scalable cloud infrastructure for AI services and APIs.
• Identify automation opportunities, streamline workflows, and continuously improve processes across the company.
• Collaborate with stakeholders to align AI solutions with organizational goals and high-value data delivery.
• Stay ahead of AI and automation trends, integrating state-of-the-art methods and tools into team projects.

• 5+ years of experience in Data Engineering, Data Operations, or Software Engineering with a proven track record of leading technical teams.
• Strong Python skills in building scalable data pipelines, automation, and backend services.
• Experience with cloud infrastructure (AWS preferred: ECS, EC2, EKS, S3, Lambda), workflow orchestration (Apache Airflow), containerization (Docker), and version control (git).
• Deep understanding of AI principles: foundation models, retrieval-augmented generation (RAG), prompt engineering, evaluation metrics, and trade-offs between different AI approaches.
• Excellent English communication skills, able to lead cross-functional teams, coordinate stakeholders, and influence technical decisions.
• Passion for innovation, building autonomous AI tools, agent networks, and scalable AI solutions in a high-growth environment.