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Build and maintain scalable data pipelines using Azure technologies and Databricks to help clients extract value from their data assets.
Rewrites and optimizes complex SQL pricing data extracts for an insurance firm, using Azure Data Factory and DevOps tools in a fully remote contract role.
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.
Build and maintain scalable data pipelines and platforms using Python, SQL, and Databricks to consolidate enterprise data for analytics and reporting.
Salary: $117734 - $146513 p.a. Data Engineer (x2) Phase one of a multi-year programme through to November 2026 Work with cutting edge technology and IT professionals Appointing salary range - $117,734 - $146,513…
Design and maintain financial data pipelines using SQL, Python, PySpark, and Microsoft Fabric to support reserving, claims, and enterprise reporting at a major insurer.
Application Development and Support ETL: Informatica, Databricks Location: Toronto, ON Time Type: Full time Job Description We’re building a relationship-oriented bank for the modern world. We need talented, passionate…
Build and maintain scalable Azure data pipelines using Azure Data Factory, Synapse, Databricks, and Fabric to transform raw data into actionable business insights.
Lead a team to design and build scalable, secure cloud data platforms on Azure and/or GCP, using Spark, Databricks, and managed services while coaching engineers and driving DataOps/FinOps practices.
Design and govern enterprise-scale AI-ready data platforms using Azure Databricks, Snowflake, and Delta Lake to enable analytics, GenAI, and ML workloads.
Build and deploy AI/ML models on Azure, integrating with Microsoft services like Teams and Graph API using Python, PyTorch, and LangChain.
Build and optimize cloud data pipelines and lakehouse solutions using Microsoft Azure and Fabric to enable scalable analytics and AI for enterprise clients.
Designs and governs enterprise-scale data platforms using Azure Databricks, Snowflake, and Lakehouse architecture to enable AI, analytics, and GenAI workloads.
Build and optimize cloud-native data platforms using Microsoft Fabric, Azure Synapse, and Python to power scalable analytics and data pipelines for a product-focused company.
Industry/Sector Not Applicable Specialism Product Innovation Management Level Manager Job Description & Summary The Opportunity Join our Acceleration Center India and help shape the future of business for our…
Designs and governs enterprise-scale data architectures for a government client, focusing on Snowflake, DBT, and modern data platforms while establishing governance, modeling standards, and AI-assisted delivery frameworks.
Build and maintain scalable data pipelines in Azure (Databricks, ADF) using Scala, Python, and SQL; design enterprise data warehouses and optimize ETL/ELT workflows for insurance and healthcare analytics.
Leads a small team of Data Engineers to build and optimize an Azure-based data platform using Fabric, Synapse, and SQL, while mentoring engineers and improving data pipelines and warehouses.
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