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Leads a data engineering team to design, build, and maintain data pipelines and services for SCOR’s IT/data products, ensuring adherence to best practices and cross-team collaboration in a (Re)insurance-focused fintech environment.
Lead a data engineering team building and maintaining data pipelines and API services for data distribution, primarily using Python, PySpark, and SQL in an agile environment at a reinsurance company.
Leads a data engineering team to design, build, and maintain data pipelines/APIs for SCOR’s insurance/financial products, ensuring scalability, documentation, and team growth while adhering to agile best practices.
Lead Data Platform Architect responsible for defining and evolving Alleima's Common Data Platform on Microsoft Fabric, covering end-to-end architecture from data ingestion to analytics across Finance, Supply Chain, Production, Quality, and Sustainability domains.
Design and maintain cloud-based data pipelines, warehouses, and lakes for a large bank, ensuring secure, accurate, and high-velocity data processing and enabling analytics and ML workflows.
The Machine Learning Engineer will develop and deploy automated ML pipelines for insurance risk modeling and pricing. The role involves using Python, MLOps tools, and TDD practices to optimize model performance and mentor junior team members.
This Data Engineer role involves building and scaling ETL/ELT pipelines within a greenfield data transformation project using Microsoft Fabric and Databricks. The position requires expertise in PySpark and SQL to develop modern data solutions and support enterprise-wide analytics.
The Data Scientist will design and deploy fraud detection models and strategies to analyze transactional anomalies and mitigate fraud risks. The role involves using Python, R, SQL, and cloud-based data platforms to develop predictive variables and automate analytics processes.
The Azure Data Engineer will design and maintain scalable cloud-based data pipelines and ETL frameworks using Azure services like ADF, Databricks, and Synapse. The role requires strong programming skills in Java or C# to build reusable components and integrate data across enterprise systems.
The Data Engineer will design, build, and maintain scalable ETL/ELT pipelines and databases to support Department of Veterans Affairs programs. The role focuses on optimizing data performance and integrity using SQL, Spark, Databricks, and Azure cloud analytics services.
Analyze large datasets using SQL, Python, Spark, and Azure to extract insights for US clients in healthcare/life sciences, ensuring data accuracy and supporting business decisions.
Builds and maintains data pipelines, warehouses, and lakehouses for Homes.com to track site performance, user behavior, and product usage, integrating AI/ML for predictive insights and business growth.
Lead large-scale data engineering and analytics program delivery across strategic accounts, overseeing end-to-end execution, architecture decisions across Azure/AWS/GCP/Snowflake/Databricks/Microsoft Fabric, and building high-performing onshore/offshore data engineering teams.
Build self-service ML platform tooling and golden paths from the ground up, enabling Data Scientists to independently deploy models to production across batch and real-time use cases using Python, PyTorch, TensorFlow, Kubernetes, and MLflow.
Senior Data Scientist building end-to-end production decision systems—forecasting, optimization, pricing, and batch/real-time recommendations—using Python, PyTorch/TensorFlow, and SQL at a lottery and sports-betting company in Toronto.
Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients,…
Designs, builds, and maintains scalable data pipelines, lakehouse architectures, and transformations using PySpark, SQL, and cloud/data tools to power enterprise analytics.
Data Engineer focused on Adobe Experience Platform, designing and building scalable data pipelines, XDM schemas, identity resolution, and customer segmentation for enterprise marketing solutions using SQL, Python, dbt, and cloud data warehouses.
Develops statistical and machine learning models to analyze complex business scenarios, quantifying uncertainty and driving data-driven decision-making for finance and enterprise management.
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