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George Dausheyev

@georgedausheyev

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I build high-performance Spark data pipelines for financial-market analytics and regulatory reporting.

Czechia

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What I'm looking for

I'm looking to continue building high-performance data pipelines and analytical systems, particularly in financial markets, regulatory reporting, and large-scale distributed data processing. I'm also interested in growing my Python, PySpark, and Databricks experience.

At Deutsche Börse, I build and maintain Scala/Spark batch pipelines and analytical alerts over exchange trading data for market-surveillance investigations. I reduced average processing time from 10 hours to 15 minutes through Spark tuning and partitioning changes, while reducing cluster network communication.

Previously at Barclays, I built distributed web applications, backend services, and Spark/NiFi transformation pipelines that delivered data for critical regulatory reports with 100% on-time compliance. At Vodafone, I developed high-throughput Scala, Kafka, and Flink services processing real-time mobile telemetry for millions of subscribers.

I bring eight years of JVM data-pipeline experience, including Scala, Spark, Hadoop, Hive, and Impala, and I’m currently expanding my Python, PySpark, and Databricks skills.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Deutsche Börse

Jan 2024 - Present (2 years 8 months)

Built and maintained Spark (Scala) batch pipelines and analytical alerts over exchange trading data for a market-surveillance service. Cut average data processing time from 10 hours to 15 minutes through Spark performance tuning and partitioning strategy changes.