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Builds and maintains ETL pipelines in Azure Databricks and SQL, curates data lakes, and serves analytics using Azure Synapse and CosmosDB.
Build and maintain AWS-based big-data pipelines for a mobility/climatetech/logistics company, validating data accuracy and ensuring secure sharing.
Build and train ML/DL models, optimize them for performance, and create scalable PySpark data pipelines using Python, PySpark, and Scikit-learn.
Build and maintain high-throughput data pipelines for a credit-scoring platform, using Python, PySpark, SQL, and Airflow to process large volumes of financial data.
Builds and optimizes data pipelines in Azure Databricks and Data Factory using PySpark, SQL, and Python to process and store data in cloud storage and databases.
Leads a team to design and deploy a multi-agent GenAI system for data-quality monitoring, using LLM agents, RAG pipelines, and Python to detect anomalies and reduce business risks.
Build autonomous AI agents and data pipelines using LangChain/LangGraph or Google Vertex AI Agent Builder to automate analytics and decision-making at scale.
Designs and builds scalable data pipelines and modern data warehouses using Microsoft Fabric, Azure, and Databricks to enable analytics and reporting.
Senior data engineer building scalable real-time and batch pipelines with Spark/PySpark and Python for backend services and APIs.
Designs and builds end-to-end data pipelines on Azure Synapse and Data Factory, modeling relational/ dimensional data in T-SQL and PySpark to deliver governed analytics platforms for clients in industrial, energy, consumer and public sectors.
Build and maintain scalable data pipelines for Plenitude’s EV-charging network, using Python, PySpark, AWS, and Databricks to feed analytics and operational tools.
Build and maintain ML models and data pipelines in Python and PySpark on AWS SageMaker, focusing on recommendation and churn prediction systems for real business impact.
Design and build scalable data pipelines and analytics models for a healthcare platform using Databricks, PySpark, SQL, and Azure to enable real-time and batch processing.
Build and maintain a Lakehouse platform using PySpark and Databricks, designing Delta Lake schemas and batch/near-real-time pipelines for reliable, scalable data solutions.
Build and maintain a PySpark and Delta Lake-based data lakehouse on Databricks, creating batch and near-real-time pipelines to power analytics and data sharing for internal products.
Builds and maintains data ingestion pipelines, lakehouse environments, and real-time streaming systems using SQL, PySpark, Kafka/Kinesis, and Go.
Builds and maintains PySpark pipelines on Databricks to power reliable data products and enrichment workflows for a SaaS analytics platform.
Senior Data Engineer builds and optimizes Spark-based data pipelines on AWS for analytics, ML, and reporting in a Madrid-based role with hybrid flexibility.
Build scalable data pipelines on Databricks and Spark for a global automotive project, using PySpark, SQL, and cloud (Azure).
Build and maintain data platforms on Databricks and cloud engines to enable clients to make efficient decisions using Python, PySpark, and SQL.
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