Analytics Engineer

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Siemens Healthineers

WebsiteLinkedInAll Job Openings

10,000+ employees

⚕️ Healthcare Insurance

🧬 Biotechnology

💰 $1.5M Grant on 2021-05

Healthcare Insurance • Biotechnology • Medical Device

Siemens Healthineers is a leading MedTech company focused on pioneering breakthroughs in healthcare. They offer a comprehensive portfolio that addresses the entire care continuum for serious diseases, including medical imaging, laboratory diagnostics, point-of-care testing, and digital health solutions. With a commitment to innovation, sustainability, and improving patient access to care, Siemens Healthineers collaborates with healthcare professionals and organizations globally to advance medical technology and enhance patient outcomes.

📋 Description

• Help transform data into trusted insights that drive business decisions • Bridge the gap between data engineering and analytics • Build scalable data models, semantic layers, and automated data pipelines that power reporting and dashboards • Work with modern technologies including Snowflake, Power BI, dbt and AI-enabled analytics platforms • Create a single source of truth for the business • Design and develop analytics-ready data models and semantic layers in Snowflake • Build scalable data transformations and automated data quality processes • Create trusted datasets and standardised KPIs that support consistent reporting • Partner with Data Engineers, BI Developers, and business stakeholders to deliver meaningful insights • Drive data governance, documentation, and business-friendly data definitions • Support self-service analytics and AI-powered reporting capabilities • Improve data reliability, performance and automation across the analytics ecosystem

🎯 Requirements

• Experience in Analytics Engineering, Data Engineering, BI Development or a similar data-focused role • Strong SQL skills and hands-on experience with Snowflake • Experience building semantic models and analytics solutions in Power BI • Understanding of data warehousing concepts, including fact and dimension modelling • Experience developing and maintaining data pipelines, transformations and testing frameworks • Familiarity with version control and modern data development practices • Interest in AI, automation and advanced analytics • Strong communication and collaboration skills

🏖️ Benefits

• Professional development opportunities • Global community that celebrates diversity and individuality