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Lead a team to modernize Unum’s data platforms using Azure, Databricks, and Kafka, building scalable pipelines and cloud/hybrid architectures to enable analytics and AI across the business.
Lead a team of data engineers to build and maintain Zoopla’s scalable data platform using Python, SQL, AWS, Redshift, Databricks, and Airflow.
Designs and maintains data pipelines using Azure Synapse, Azure Data Factory, and SQL tools to support analytics in a manufacturing-focused compliance company.
Lead the design, build and operation of a large-scale AWS data platform using Redshift, Glue, Lambda and Kinesis to deliver reliable analytics and insights for the UK rail industry.
Build and optimize data pipelines using PySpark, Azure Databricks, and cloud platforms to deliver scalable analytics solutions for enterprise clients.
Senior Consultant designs and delivers modern data platforms using Microsoft Fabric, Azure Databricks, and Power BI, leading client engagements to turn data into business insights.
Design and build scalable AWS data pipelines (ETL, data lakes, warehouses) using Python, Spark, and AWS services like Glue, RedShift, and Kinesis to process large datasets for clients across multiple sectors.
Build and maintain data pipelines, ETL/ELT processes, and a central data lake to support reporting and analytics for a London-based organisation undergoing data transformation.
Builds and maintains scalable Azure data pipelines and lakes using Python, PySpark, SQL, Azure Data Factory and Microsoft Fabric for UK public-sector projects.
Build and maintain scalable data pipelines using Azure technologies and Databricks to help clients extract value from their data assets.
Build secure, scalable data pipelines and AI-ready platforms for Defence customers using Python, Kafka, Spark, and Kubernetes in air-gapped environments.
Build and maintain cloud-based data pipelines and warehouses using Azure Databricks, Snowflake, and AWS services to enable AI/ML-driven insights for enterprise clients.
Build and maintain scalable data pipelines and AI-ready datasets for analytics and agentic systems using cloud platforms like AWS/Azure/GCP and tools such as Databricks and Snowflake.
Design and maintain cloud data pipelines on AWS, build ETL/ELT workflows, and optimize Snowflake data warehouses using PySpark, dbt, and SQL for analytics in regulated industries.
Design, build, and maintain scalable data pipelines and cloud-based data platforms in AWS, Snowflake, and Azure using DevOps practices, CI/CD, and infrastructure-as-code.
Build and maintain scalable data pipelines and platforms using Python, SQL, and Databricks to consolidate enterprise data for analytics and reporting.
Build and maintain Python-based APIs and data infrastructure that power energy-market analytics and an LLM-driven AI Analyst, using AWS, Terraform, and streaming systems.
Builds and configures a government Databricks workspace, designs data pipelines from enterprise systems, and implements Unity Catalog and MLflow for governance and ML workflows.
Lead the architecture and development of Pantheon’s data platform, extending it to surface insights in products and power ML/LLM-driven features using Python, Snowflake, Airflow, Kubernetes, and Terraform.
Build a unified analytics web app in C#/.NET and Angular, integrating PowerBI and AI-assisted data chat, while migrating legacy reporting features into a scalable, multi-tenant microservices architecture.
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