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Builds end-to-end data pipelines on Databricks using Python and PySpark to process large-scale datasets in a distributed Spark environment.
Design and implement Azure-based streaming-to-batch data pipelines using Data Factory, Data Lake Storage, and PySpark/Scala in Python.
Build and maintain data pipelines and distributed systems for European clients, using Python, Spark, and cloud platforms to solve business challenges in industries like pharma, insurance, and manufacturing.
Build and maintain data ingestion/ETL pipelines using Python, PySpark and Spark, load into Redshift, and support BI reporting in a growing product team.
Build and maintain AI-driven data pipelines for financial crime detection at a fintech company using Spark, Python, and big-data tools.
Build and maintain cloud-based data platforms on AWS using PySpark, Python, and dbt to ingest, process, and orchestrate batch and streaming pipelines for clients.
Build and maintain scalable data pipelines using Microsoft Fabric to integrate and optimize data from ERP, CRM, and APIs for analytics and reporting.
Senior Data Engineer building scalable big-data pipelines in AWS using Spark on Scala, optimizing performance for large datasets and collaborating with an international team.
Senior Data Engineer builds and scales a modern data platform using Databricks, PySpark, and Azure Data Factory to power advanced analytics, ML models, and near-real-time decision systems.
Build and maintain data pipelines, manage distributed databases, and support development teams using SQL, PySpark, and streaming tech like Kafka.
Build and maintain scalable data pipelines and infrastructure using Databricks, Spark, ClickHouse, and Kafka to power real-time analytics and ML for mobile app monetization.
Build and maintain AWS-based data pipelines using Python, PySpark, and SQL to integrate, transform, and deliver clean, scalable data for business insights.
Build and evolve a global data platform using Microsoft Fabric, lakehouse architecture, and Azure, designing scalable pipelines and reusable data models for analytics and AI.
Senior PySpark Data Engineer builds and optimizes data pipelines in cloud environments (AWS/Azure) using PySpark, Hadoop, and SQL Server for clients across industries.
Design and maintain scalable data pipelines and ETL/ELT workflows using Databricks, Azure Data Factory, and PySpark for cloud-based data platforms.
Build and maintain data pipelines using Spark, PySpark, and AWS services to process batch and real-time data for clients.
Lead Data Engineer defines data processes, ensures end-to-end traceability, and bridges business needs with technical teams in a banking client, using Airflow, PySpark, Kafka, and AWS.
Design and maintain Snowflake-based data pipelines and warehouses that feed credit risk models, analytics, and reporting for a global distributor’s credit function.
Designs and maintains cloud-based data pipelines and warehouses using Python, PySpark, SQL, and Databricks to power analytics and ML on Microsoft Azure.
Build and optimize Azure-based data pipelines and architectures, implementing scalable cloud solutions with Azure Data Factory, Databricks, and PySpark.
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