Data Analyst (m/f/d)

METYCLE · Cologne (GER)mid

En corto

▸Analista de datos que convierte datos operativos y de negocio en insights accionables.
▸Trabaja con equipos de operaciones, trading y tecnología para mejorar procesos usando SQL, visualización y modelos de datos.
▸Destaca por transformar datos imperfectos en fuentes confiables de verdad para la organización.

Fluent English required for collaboration with international teams.

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¿Qué piden?

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

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

SQLExcelData Warehousedbt Docsdashboardsreportingdata modellingdata quality checksdata lineageautomated reporting

¿A quién escribirle en METYCLE?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

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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