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! Our SmartSorting Hubs combine advanced sorting technology, automation and AI to transform how complex scrap is processed, turning selected mixed streams into better-defined industrial feedstock while improving material quality and traceability.
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.
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.
- 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.
- Documentation & Standards: Maintain clear documentation for datasets, transformations, metrics, and data lineage using dbt Docs or similar tools, and contribute to practical standards for SQL, data modelling, testing, and visualisation.
- Automation & AI: Identify manual or inefficient analytical workflows and improve them through automation, modern data tooling, and AI-assisted analysis - using AI to accelerate data exploration, querying, documentation, and reporting while maintaining a strong understanding of and control over the underlying data.
- 3+ years of hands-on experience in Data Analytics, Product Analytics, Business Analytics, or a closely related analytical role, with a track record of turning complex business questions and raw data into reliable analysis, actionable insights, and business decisions
- Strong analytical and statistical thinking, with the ability to identify trends, anomalies, and root causes, define meaningful metrics, challenge assumptions, and work confidently with imperfect or incomplete data
- Independent, structured, and pragmatic, with a strong sense of ownership. You are equally comfortable working with business stakeholders and engineers, communicate clearly across different levels and functions, and can bridge the gap between business needs and technical solutions. You are also genuinely curious about AI-assisted analytics and modern cloud data workflows, while maintaining full control of and understanding of the underlying data
- Strong business understanding and analytical curiosity, with the ability to quickly grasp the essentials of a complex, finance-driven business, understand how the underlying processes work, and translate business needs into meaningful analytical questions. Experience with financials, commodity trading, finance analytics, or accounting is a strong advantage
- Strong SQL skills with experience working with complex datasets, data transformations, joins, aggregations, window functions, and analytical data models
- Proven experience working with modern Data Warehouses such as Snowflake, BigQuery, Redshift, Databricks, or similar, including building and maintaining clean, reliable datasets for analysis and reporting
- Experience with modern analytics engineering practices and tools such as dbt, including data modelling, automated data quality tests, documentation, and data lineage
- Strong experience with BI and visualisation tools (e.g. Metabase, Looker, Tableau, Power BI or similar), with a focus on building clear, performant dashboards and enabling self-service analytics
- You will have the opportunity to challenge the status quo and work on an innovative venture with significant impact
- You will be able to take ownership and shape the future of metal recycling and green energy solutions at an early stage
- We offer a competitive salary including virtual company shares
- We offer an environment with flat hierarchies and a steep learning curve with exciting growth opportunities
- You will benefit from flexible working hours and the opportunity to work remotely or from a shared office location
- We promote an inclusive, diverse and supportive work environment
Discover more about METYCLE:
About us | LinkedInWe look forward to receiving your application. Irene Prinz is happy to answer any questions you may have: +49 152 34 62 72 85.