Senior
Data Engineer
CELSA es el primer productor europeo de acero circular de bajas emisiones y constituye la cadena de suministro circular más grande de Europa. Recicla chatarra férrica para producir acero en hornos de arco eléctrico, usando la tecnología más sostenible y la más eficiente energéticamente.
About CELSA
We’re Europe’s leading producer of circular, low-emission steel and its largest circular supply chains. We recycle ferrous scrap into new steel through electric arc furnaces, one of the most energy-efficient steelmaking routes available. Founded as a family business near Barcelona in 1967, the Group today brings together ~5,000 people and produces 5.7 million tons of steel annually, made with ~95% recycled content and designed to be 100% recyclable
Our purpose extends beyond steel: making the cleanest way to produce it also the smartest – and data, analytics and artificial intelligence are central to that ambition.
We are embedding AI into core steelmaking operations, powered by clean, connected and reliable data flowing between plant floor, cloud and decision-making systems. This is where this role can create meaningful impact.
The role offers a foundational opportunity with significant scope, as the Group builds a unified data lake on a modern Azure and Databricks stack, connecting melt shops, scrap yards and commercial operations. The data products developed in this role can go beyond individual reporting use cases, forming core foundations for scaling the Group’s broader AI program.
What you’ll do
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Design, build and maintain scalable data pipelines across the data lake’s raw, enriched and curated layers
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Connect the OT and IT worlds – integrate sensor & historian data from PLCs and edge systems (Siemens Industrial Edge, Kafka) with SAP and beyond, batch and real-time
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Build and operate our Azure & Databricks platform – standardized ETL, data cataloging, metadata & lineage (Unity Catalog, Purview)
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Partner with data scientists to productionize models – the reliable, API-driven pipelines they need to run and retrain
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Create reusable, documented data products that accelerate every use case and plant
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Work with architecture & security to keep data flows, especially from OT assets
What we’re looking for – must-haves
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A technical degree (Computer Science, Software Engineering, Telecommunications, Mathematics or similar), with the experience to match: PhD + ~4 years, MSc + ~6 years, or BSc + ~8 years building production data pipelines and platforms
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Strong SQL and Python, with solid large-data and ETL / ELT experience
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Hands-on with cloud data platforms and lake / lakehouse concepts (raw / enriched / curated layers, cataloging, lineage)
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A pragmatic engineering mindset – you build things that work, that others can maintain, that scale
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Proactive and structured, comfortable working across multidisciplinary teams
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High level of English
Bonus points
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Azure & Databricks specifically (strongly preferred)
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Streaming & integration tech (Kafka)
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OT / industrial data, historians or edge architectures
Not every requirement needs to be met in full. The criteria above reflect an ideal profile, while career paths often develop in less linear ways and strong candidates may not align with every item on a list. If this role is exciting and most of the profile feels aligned, we would value hearing from interested candidates rather than seeing them self-select out. We would welcome hearing what you have built.
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