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Builds and optimizes data pipelines to automate scientific content generation, using Spark/Hadoop and cloud solutions to reduce manual entry and improve data consistency.
Build and maintain scalable data pipelines and configure Quantexa’s decision-making platform using Spark, Scala, and cloud services to help clients in banking, healthcare, and government detect fraud and manage risk.
Builds and maintains ETL pipelines using Spark, Hadoop, and cloud tools to process business data, ensuring performance and scalability.
Build and optimize large-scale data pipelines for aerospace and defense clients using Python, Spark, and PostgreSQL on Cloudera/Hadoop clusters.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and optimize data workflows for enterprise clients.
Designs and maintains scalable data pipelines, ETL/ELT processes, and cloud-based data platforms to support analytics and AI in high-security sectors like defense.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and transform data for clients.
Design and maintain data pipelines and ETL processes to support AI/ML models and quantum computing applications using Python, SQL, and cloud platforms.
Build and maintain cloud-based data pipelines and ETL processes to deliver clean, accessible datasets for enterprise clients in advertising and marketing technology.
Design and maintain scalable data pipelines and warehouses for a global ad-tech platform, ensuring real-time data availability and quality for analytics and decision-making.
Build and maintain scalable data pipelines and platforms using Spark, Scala, Kafka, and cloud tech to enable analytics and decision-making across BNP Paribas.
Senior Data Engineer builds scalable data pipelines, ETL/ELT processes, and cloud-based analytics platforms using Python, Spark, AWS, and modern data stacks to power AI-driven solutions.
Build and maintain cloud-based data pipelines and analytics platforms using Python, SQL, Spark, and BigData tools to deliver business insights.
Senior PySpark Data Engineer builds and optimizes data pipelines in cloud environments (AWS/Azure) using PySpark, Hadoop, and SQL Server for clients across industries.
Build and maintain AI-driven data pipelines for financial crime detection at a fintech company using Spark, Python, and big-data tools.
Designs and builds real-time data pipelines and lakehouse architectures using Hadoop, Kafka, Python, and Java.
Build and maintain scalable data pipelines for a major bank using Java, Spark, and cloud-based Hadoop tools like Cloudera.
Build and maintain cloud-based data pipelines and analytics solutions on AWS using Python and SQL, integrating AI models into business-facing data systems.
Senior Data Engineer builds scalable pipelines, modernizes LLM architectures, and implements RAG systems to enhance data quality and enable advanced analytics for a telecom group.
Builds and maintains ETL pipelines and data warehouses on GCP to power AI-driven marketing, using Python, dbt, Airbyte, and Airflow.
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