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Data engineer building BI and Big Data solutions for ProRail's logistics department, migrating on-premise BI to Azure Synapse and Microsoft Fabric, and developing scalable data pipelines with PySpark and SQL.
Data Engineering Associate building production data platforms—ETL pipelines, data lakes, and streaming hubs—primarily on Azure (Databricks, Data Factory, Synapse) using SQL, Python/PySpark, Airflow, and Kubernetes for a consulting firm in Amsterdam.
Build and maintain data pipelines and the Azure/Databricks data platform for a beverage distribution company expanding into Belgium.
Designs, develops, and optimizes Azure-based infrastructure for data pipelines and DevOps workflows, focusing on IaC, CI/CD, and data processing with Python/PySpark.
job summary: Responsibilities Data Engineer with experience designing scalable data pipelines, ETL workflows, and cloud-based analytics solutions. Robust expertise in Python, SQL, PySpark, Databricks and AWS services…
Builds and optimizes data pipelines on Azure/Data Lake using PySpark/Scala for large-scale batch processing, ensuring cost-efficient distributed workflows and production deployments with DevSecOps.
Birlasoft is hiring a Data Engineer in Madrid to design and build data pipelines using Python, PySpark, SQL, and AWS services. The role involves using Airflow for orchestration and Docker/ECS for containerization in a 12-month contract position.
AWS Data Engineer for a stable project in Spain, building and orchestrating data pipelines using Spark, Python, SQL, Airflow, Docker/ECS, Kafka, and dbt.
The Senior Data Science Engineer will own the full lifecycle of risk detection systems, building and deploying LLM and classical ML models within a SaaS platform. The role requires a blend of data engineering, MLOps, and applied machine learning to develop scalable pipelines and production-ready AI solutions.
Senior Data Engineer responsible for scaling Sund & Bælt's Databricks-based data platform, building data pipelines and models, and enabling data and AI across the organization using Databricks, Azure, Python, SQL, and PySpark.
Senior Data Engineer building and scaling Sund & Bælt's Databricks-based data platform, designing data pipelines and models to support reporting, AI/ML, and self-service analytics using Databricks, Azure, Python, SQL, and PySpark.
Automation Test Engineer validating ETL pipelines, data warehouses, and backend systems using SQL and Python on AWS/Databricks cloud platforms within an Agile Scrum team.
At Livefront, we help companies design and build world-class digital products that command attention and inspire joy. We’ve helped household names like CVS, Samsung, General Mills, and Optum create experiences that…
Lead the architecture and implementation of enterprise metadata management solutions using Ab Initio Metadata Hub, Databricks, Unity Catalog, and Delta Lake, focusing on metadata governance, lineage, stewardship, and impact analysis.
This role involves designing and developing enterprise-scale data solutions using Databricks and medallion architecture. The engineer will build reusable frameworks, manage batch and streaming pipelines, and collaborate with stakeholders to modernize data capabilities.
Designs, builds, and scales Dataiku DSS platforms to prepare, transform, and operationalize data for analytics and AI use cases in a production environment.
Confirmed Data Engineer at a Paris-based consulting firm, designing and industrializing cloud data platforms and robust data pipelines using Spark, PySpark, SQL, Airflow, Databricks, and cloud providers (Azure/AWS/GCP), while mentoring junior engineers.
Onyx-Conseil recherche un Data Engineer pour une mission freelance basée à Nantes. Le candidat doit maîtriser PySpark et Scala et avoir une solide expérience dans l'environnement. Localisation: Nantes. Mode de…
Lead a team migrating legacy data architectures to a modern Databricks/Azure platform, building scalable pipelines and advanced analytics solutions for a large client.
The Data Engineer will design, develop, and optimize data pipelines and architectures using Snowflake, Python, and SQL. The role involves managing the full data lifecycle, from ingestion to transformation, while ensuring data quality and system performance.
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