Data Analytics Engineer

To support the expansion of IoT Data Products for the Factory Data Cloud across global Transformer factories, Siemens Energy is seeking an Analytics Engineer to join the Data & Cloud Infrastructure team under Process Digitalization in Germany. To address this business aim, this role focuses on designing scalable data models, defining standardized KPIs, and creating reusable data products within a modern, AI-enabled Data Mesh architecture. Given the focus on scalable data products, the ideal candidate will have 2-3 years of hands-on experience in production data modeling, strong SQL skills, and proficiency with dbt and Snowflake within a manufacturing or industrial context. What You Need To Make a Difference

• 40% Data Modeling & Product Development
• Own data products end-to-end, from understanding business requirements to delivering tested, documented, and production-ready transformation logic.
• Shape and apply a layered modeling approach (medallion architecture, dimensional modeling) to ensure consistent, reusable, and easily evolvable data products.
• Translate requirements from global factories and business functions into standardized definitions and shared KPIs.
• 30% Data Quality & Engineering Standards
• Build data quality checks, maintainability standards, and governance into data solutions from the start.
• Contribute to the team’s engineering standards through code reviews, shared patterns, and continuous improvement of the analytics stack.
• 30% Collaboration & Platform Integration
• Support the Factory Data Cloud (Data Mesh) implementation across more than 30 global manufacturing sites to turn operational and IoT data into trusted assets.
• Partner with Data Engineers, Product Owners, and domain experts to bridge the gap between business needs and technical solutions.

Certifications

• dbt Certified Developer
• Snowflake SnowPro Core Certification

• Academic degree in Data Analytics, Computer Science, Information Systems, Data and Process Management, or a comparable discipline.
• 2-3 years of hands-on experience developing and operating analytics or data warehouse models in production, including dbt and Snowflake.

Skills

• Data Modeling & Engineering
• Dimensional Modeling
• Medallion Architecture (layered data modeling)
• Advanced SQL
• dbt (Data Build Tool)