Analytics Engineer (w/m/d) — Möbel Pfister AG

Full description

Analytics Engineer (w/m/d) Description At pfister, we are pursuing a vision: We want to move our products into every Swiss home.We are looking for active support for this. Help us bring the approximately 100,000 products of our range to the home of our customers. Whether in one of the 18 branches or in the headquarters in Suhr: You will find a unique environment, work with appealing products and, not least, appreciation and respect for your work. At pfister, around 1,400 people are already working today - will you join us soon?

• What we offer:
• A small team with short decision-making paths and direct connection to the management
• Your work is directly involved in management decisions and operational processes
• We use AI productively in everyday work (e.g. for analysis and automation) and continue to expand
• broad spectrum of topics: infrastructure, CRM and campaigns, NPS, Pricing — and much more
• A modern data stack on Azure that we actively build — including ongoing migration projects; you can help shape architecture and tooling
• Building and continuously developing a future-oriented database as a basis for information-based and customer-oriented decisions throughout the company
• Conception, development and operation of modern data pipelines, as well as ETL/ELT processes and active data architecture
• Development of data-driven models, analyses and recommendations for action with direct added value for strategic and operational decisions
• Technical management of expansion and implementation projects and participation in the implementation of innovative technical and analytical solutions
• Close cooperation with internal stakeholders and data science experts as competent contact person and sparring partner
• Experience in data engineering, especially in the development of data pipelines and in the handling of cloud data warehouse
• Very good SQL knowledge and sound experience withrival databases
• good Python knowledge for the development and automation of data-related processes
• Analytic, structured and independent working methods with high data affinity
• Completed studies in (economic)informatics, statistics, mathematics or comparable training
• experience in the field of data science / statistical modelling
• experience in project management