European B2B Technology Scale-up
Build the data foundations that AI products actually depend on. We are working with a European B2B technology company building software for asset-intensive businesses. Its platform connects operational, IoT and business data to help customers reduce energy consumption, prevent downtime and make better day-to-day decisions.
The company has grown beyond the early start-up phase, with more than 300 people across several European markets, real enterprise customers and a product handling an increasingly complex mix of structured, semi-structured and real-time data.
Now the Data & AI team is moving from analytics-focused infrastructure towards a platform capable of supporting machine learning and AI-powered product features at scale.
As a Data & AI Engineer , you'll build and operate the data systems behind both analytics and AI use cases.
You'll work on production pipelines, cloud infrastructure, data quality, orchestration and the datasets that ML and AI services consume.
You'll work closely with Data Engineers, AI Engineers, Product and Platform Engineering,



and you'll own pieces of the platform from design through production.
Design, build and maintain reliable batch and event-driven data pipelines.
Build reusable data products that serve analytics, ML and AI workloads.
Work with structured and unstructured data coming from APIs, operational systems, IoT sources and internal applications.
Develop production-grade services and pipelines using Python and SQL .
Build and evolve cloud infrastructure using services such as S3, Lambda, Glue, RDS and Step Functions .
Manage infrastructure through Terraform or CloudFormation .
Build CI/CD workflows with GitHub Actions .
Introduce data quality checks, observability, lineage and sensible alerting.
Core: Python, SQL, AWS, Git, CI/CD
Data: S3, Glue, RDS, Spark, orchestration
Infrastructure: Terraform / CloudFormation, GitHub Actions
Observability: logs, metrics, data-quality monitoring
AI-facing d

📌 AI Data Science Engineer (España)
🏢 Value Crew
📍 España