Das ist der Job
Design, deploy, and maintain scalable cloud infrastructure for AI services and APIs.
Darum lohnt es sich
Your Tasks Lead and mentor a team of Data and AI engineers, setting objectives, reviewing code, and fostering professional growth. Stay ahead of AI and automation trends, integrating state-of-the-art methods and tools into team projects.
Your Profile 5+ years of experience in Data Engineering, Data Operations, or Software Engineering with a proven track record of leading technical teams. Excellent English communication skills, able to lead cross‑functional teams, coordinate stakeholders, and influence technical decisions.
What we offer In addition to our great team, culture, and our shared goal of empowering people with data, there are many other things that make Statista a great place to work!
Join us and benefit from: Work from abroad up to 30 calendar days a year Hybrid work and flex‑time International team and social events Subsidized urban mobility and access to fitness and wellness options Free access to Langdock and all its amazing functionalities Career & training opportunities Attractive locations and modern offices Mental health support with OpenUp Some of the benefits listed here apply only to the German entity and to Junior-level roles or above. #J-18808-Ljbffr 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.
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. 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. Passion for innovation, building autonomous AI tools, agent networks, and scalable AI solutions in a high‑growth environment.
