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Azure Data Engineer: Databricks Lakehouse & Data Pipelines
Designs and builds scalable Azure Databricks pipelines using PySpark and Delta Lake to implement ETL/ELT frameworks across a lakehouse architecture.
Azure Data Engineer - Databricks
Builds and optimizes scalable data pipelines on Azure using Databricks, PySpark, Delta Lake, and related services for ETL/ELT and streaming workloads.
Junior Data & Analytics Engineer - Microsoft Fabric / Azure
Builds and maintains the data pipelines and Lakehouse/Warehouse models in Microsoft Fabric for a mobility group’s BI modernization, using PySpark, Data Factory, and Medallion architecture.
Data Engineer with German - Senior - EY GDS Spain - Hybrid
Senior Data Engineer builds and maintains scalable batch/streaming pipelines (PySpark, SQL) for EY GDS Spain, supporting clients’ digital transformation with distributed data processing and ETL/ELT workflows.
Senior Databricks Data Engineer — Hybrid, Global Impact
Build and maintain scalable data platforms on Databricks and cloud (Azure/AWS/GCP) to enable data-driven decisions for clients and partners.
Remote Azure Data Engineer — ADF, PySpark, CI/CD
Build and maintain cloud data pipelines in Azure, using ADF and PySpark to migrate and transform data while ensuring quality and integrity.
Senior Data Engineer (Databricks) - EY GDS Spain - Hybrid
Build and maintain scalable data platforms on Databricks and cloud providers (Azure/GCP/AWS) to enable data-driven decision-making for EY clients.
Data Engineer (German) - Hybrid & Impact
Senior Data Engineer builds and maintains scalable data pipelines using PySpark and distributed tech in a hybrid role at EY GDS Spain.
Azure Data Engineer/Remoto ESPAÑA(H/M/X)
Builds and maintains cloud data pipelines in Azure, migrating and transforming data with ADF, PySpark and Python while collaborating with analysts and architects.
Data Engineer
Salary: £68,000 - 108,000 per year Requirements: Banking experience required Hands-on experience with Databricks, Spark/PySpark, Python, and SQL Experience developing and maintaining data pipelines and data processing…
Senior/Lead Data Engineer
Salary: £? - ? per year Requirements: Strong Spark and PySpark engineering experience Experience developing and modernising large-scale data pipelines Strong Python skills and software engineering fundamentals…
Coordinador/a de Data Science | IA, Machine Learning & Advanced Analytics | Madrid (Híbrido)
Leads end-to-end Data Science projects, coordinating cross-functional teams to build and deploy ML/AI solutions (including generative AI agents) for healthcare insurance, while defining KPIs and ensuring business-aligned impact.
Machine Learning Engineer | Python | AWS | SageMaker | PySpark | SQL | Sector Bancario
Build, train, and deploy ML models end-to-end for a major bank using Python, PySpark, SQL, and AWS SageMaker on cloud infrastructure.
Python software engineer
Builds and maintains Python-based data loads and backend processes for high-level banking projects in a hybrid role.
Senior Data Engineer
Design scalable data architectures and ETL pipelines for a leading insurance company, using multi-cloud tools (AWS/Azure/GCP), Databricks, Python, PySpark, and SQL to enable analytics and reporting.
Data Engineer
Builds and maintains data pipelines using Python, Spark, and Databricks to move and process large datasets in cloud environments like Azure, AWS, or GCP.
Data Engineer - Ms Fabric
Build and optimize data pipelines using Databricks, PySpark, and SQL to create a data lakehouse architecture for Trade Marketing analytics.
Data Engineer - Power BI, Microsoft Fabric, PySpark
Builds and optimizes data models and pipelines for an insurance client using Power BI, Microsoft Fabric, PySpark, and SQL to power analytics and dashboards.
Data Engineer: Power BI, PySpark & Fabric Architect
Designs and maintains analytical data models, builds transformations, and optimizes Power BI dashboards using SQL, PySpark, and DAX.
Principal Consultant - Lead Data Analyst
Lead a financial-services data platform project, designing canonical models in AWS/Databricks to standardize complex relational data and enable reporting, reconciliation and automated outputs.