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Senior Data Engineer building and maintaining a modern Lakehouse data platform using Databricks, Airflow, and PySpark pipelines with a focus on data governance and lineage.
Build and maintain data pipelines in Microsoft Fabric, model insurance-brokerage data, and deliver clean datasets for BI, analytics, and regulatory reporting.
Design and build scalable data pipelines and cloud-based data platforms using PySpark, Snowflake, and Databricks to support AI and analytics initiatives.
Build and maintain scalable data pipelines on Microsoft Azure and Databricks using PySpark, SQL, and CI/CD, while collaborating with cross-functional teams to deliver end-to-end data solutions.
Design and deploy large-scale data pipelines on Azure Databricks using PySpark, evolving the data architecture for a major ESN client.
Build and maintain scalable data pipelines using Python, SQL, Spark, and cloud services (Azure/AWS/GCP) to deliver clean, reliable datasets for analytics and AI teams.
Build and optimize scalable data pipelines on Databricks and cloud platforms, transforming raw data into automated, production-ready analytics and AI infrastructure using Python, Spark, and IaC.
Designs and maintains scalable cloud-based data pipelines and storage using Python, SQL, and cloud platforms like Azure/AWS/GCP to ensure reliable, high-quality data for business operations.
Build and maintain scalable data pipelines in Python/PySpark on AWS to ingest, transform, and expose market data for anomaly detection in a fintech setting.
Build and maintain scalable data pipelines on Microsoft Fabric, optimizing performance and ensuring data quality for Groupe Premium.
Build and scale a cloud-native data platform on AWS, driving real-time analytics, personalization, and AI-powered data products for millions of users.
Build and maintain ETL/ELT pipelines in Python and Spark/Scala to transform healthcare reference data into reliable datasets for SaaS products and partners, while collaborating with AI engineers and product teams.
Build and maintain ETL/ELT pipelines in Python and Spark/Scala that transform healthcare data into reliable datasets for SaaS products, using FastAPI, Airflow, dbt, and AWS.
Build and maintain ETL/ELT pipelines in Python and Spark/Scala to transform healthcare data into reliable datasets for SaaS products, using FastAPI, Airflow, dbt, and AWS.
Principal Backend Engineer builds and shapes the data/AI backend for a marketing automation platform, writing Python services on AWS serverless and leading Databricks medallion pipelines to power AI-assisted analyst workflows.
Build and maintain AWS-based microservices in Python (FastAPI/Flask) to power secure device-financing platforms used globally, focusing on Lambda, SQS, API Gateway, and event-driven workflows.
Design and maintain data pipelines for financial datasets using Python, PySpark, and AWS services like Databricks, ensuring data quality and security for regulatory reporting.
Design and build cloud-scale data pipelines on Databricks using PySpark and Python, then lead teams to deliver end-to-end data transformations for UK clients.
Leads data engineering teams to build AI-driven pipelines and data foundations for an energy-trading firm using Databricks, PySpark, Python, and Azure.
Principal Data Engineer designs and builds scalable data pipelines on Databricks/AWS or Azure, using PySpark, SQL, and Delta Lake to migrate customers to cloud data platforms.
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