Data Analyst (m/f/d)

METYCLE·Cologne (GER)mid

In short

→Analista de datos que convierte datos operativos y comerciales en insights accionables.
→Trabaja directamente con equipos para entender necesidades, limpiar datos y construir dashboards y modelos de datos confiables.
→Destaca por su rol clave en automatizar reporting y mejorar calidad de datos en una industria de metales secundarios sostenible.

Experiencia trabajando con equipos internacionales y comunicación efectiva en inglés.

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What they ask for

✓Experiencia práctica en análisis de datos y SQL.
✓Capacidad para trabajar con grandes conjuntos de datos imperfectos.
✓Habilidades en visualización de datos y creación de dashboards.
✓Experiencia en modelado de datos y definición de métricas claras.
✓Colaboración con equipos técnicos y no técnicos para traducir necesidades en soluciones analíticas.
✓Conocimiento en calidad de datos y validación de información.

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SQLExcelDashboardsData Warehousedbt DocsAIAutomationData ModellingData Quality ChecksSelf-Service Analytics

Who should you write to at METYCLE?

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ABOUT US METYCLE: where innovation meets sustainability We are reshaping the global secondary metals industry to accelerate the circular flow of metals. By combining global trading, advanced processing and digital intelligence, we make secondary metals more predictable, transparent and scalable, strengthening industrial supply chains and reducing reliance on primary metal production. And the impact is significant: recycling aluminium can reduce greenhouse gas emissions by up to 95% compared with primary aluminium production. And we take it further! Join us at a defining stage as we bring the $600 billion scrap metals industry into the 21st century and build a new global standard for secondary metals. READY TO MAKE AN IMPACT? We are looking for an experienced Data Analyst who turns complex operational and business data into clear insights, better decisions, and measurable improvements. You bring strong hands-on experience in data analysis, SQL, visualisation, and working with large and imperfect datasets - and understand how to connect data to real-world processes and business outcomes. This is an integrated role at the intersection of business, operations, and technology. You’ll work directly with teams to understand their data needs, dig into the details hands-on, and find the right way to answer their questions - whether through SQL, Excel, dashboards, or other tools. You’ll also translate recurring needs into requirements for Engineering and help build stable, automated reporting and analytics over time, particularly across our trading business. Join our international team and play a key role in shaping innovative solutions for scrap metal processing - using data and technology to build a more efficient and sustainable future. YOUR MISSION Analytics & Insights: Turn complex business questions into clear, actionable analysis, identifying trends, opportunities, risks, and the key drivers behind business performance. Work directly with the people who have the data need to understand their questions, challenge assumptions, and turn raw data into meaningful insights and decisions. Data Foundations: Build and maintain the data transformations needed to turn raw data into clean, reliable, analysis-ready datasets in the Data Warehouse. Work hands-on with imperfect data, validate its accuracy and meaning, and identify gaps or inconsistencies in how data is captured. Data Modelling: Translate business requirements into well-structured, reusable data models and clearly defined metrics that provide a trusted source of truth for analytics across the organisation. Data Quality: Implement and maintain data quality checks and tests to ensure data is accurate, consistent, complete, and fresh - proactively identifying and resolving issues with relevant stakeholders and working with Engineering to improve how underlying data is captured. Reporting & Self-Service: Build and support dashboards, reports, and analytical datasets that are intuitive, performant, and optimised for internal reporting and self-service analytics. Help turn recurring analytical needs and ad-hoc analysis into stable, scalable, and increasingly automated reporting. Stakeholder Partnership: Work closely with Product, Operations, Finance, Marketing, Engineering, and other teams to understand business needs, challenge assumptions, and translate them into meaningful analytical questions and solutions. Communicate effectively across different levels and functions, from discussing detailed data questions with technical teams to presenting clear insights and recommendations to senior stakeholders.

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