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Design and build scalable data pipelines to process and store banking data, ensuring availability and quality for analytics and reporting.
Build and maintain scalable data pipelines and warehouses using SQL, Python, and cloud platforms to support analytics and reporting.
Designs and maintains data pipelines and systems using SQL, Spark, Python, and Azure tools to process and analyze raw data for business insights.
Data Scientist builds and optimizes data pipelines on GCP BigQuery and Python to support banking analytics and reporting.
Designs and builds scalable big-data infrastructure and ETL pipelines using Python, Spark, and cloud services to support reporting and analytics.
Build and maintain scalable data pipelines using Databricks, GCP, and Azure to power AI models, RAG search, and analytics for a global enterprise.
Designs and maintains scalable data pipelines using Snowflake, dbt, Airflow, and AWS to power enterprise analytics platforms.
Build and maintain Snowflake data pipelines that move financial data between Oracle and client warehouses, enabling ESG reporting and analytics with Row Level Security.
Designs and builds scalable cloud data platforms across AWS, Azure, and GCP, leading AI-driven data pipelines and architectures for enterprise clients.
Senior Data Engineer builds and maintains scalable data pipelines and analytics platforms for an educational publisher, ensuring data quality and security.
Maintains and modernizes data architecture (SQL Server, Power BI, SSRS), builds ETL pipelines, models data, and supports dashboards for global clients.
Build and deploy AI-driven analytics, automation, and data solutions to streamline reinsurance operations using Python, SQL, Power BI, and C#/.NET.
Build and scale production-grade data pipelines and Lakehouse infrastructure using Azure, Databricks, Python, and Spark to power analytics and AI for enterprise risk and financial advisory services.
Build and maintain Python-based data pipelines, integrate APIs, and create Power BI dashboards to automate reporting and analytics workflows.
Lead the design and architecture of Kueski’s data platform, ensuring scalable, high-quality data systems using Python, SQL, Spark, and AWS.
Build and maintain data services and backend integrations for airline and rail customers using C#/.NET, SQL, APIs, and cloud platforms like Azure.
Designs and maintains AWS-based data pipelines and cloud infrastructure using Python, SQL, and IaC, ensuring secure, scalable data solutions.
Build and maintain robotics data pipelines, ML training systems, and real-time tools for autonomous vehicles and embodied AI, using Python, C++, React, and cloud infrastructure.
Build and maintain data-visualization dashboards and ETL pipelines for hazardous-waste tracking and reporting.
Builds and scales a Microsoft Fabric-based data lakehouse, integrating Dataverse and enterprise systems, and enabling Power BI reporting and AI initiatives.
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