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Senior Data Scientist builds and maintains Azure data pipelines, deploys ML models, and sets up MLOps for a 12-month client engagement in Cape Town.
Lead a team to design and build scalable data platforms using Microsoft Fabric, Databricks, and Azure, enabling enterprise analytics and governance.
Build and optimize ETL pipelines, data models, and APIs for a multi-tenant financial-services data platform using Python, SQL, Azure Data Factory, Synapse, and Data Lake.
Lead the design and build of enterprise-scale data platforms using cloud tools (AWS/Azure), SQL, Python, Spark, and orchestration (Airflow) to deliver reliable, analytics-ready data for BI, AI, and reporting.
Build and maintain scalable data pipelines and lakehouse solutions on Azure/Databricks to deliver trusted datasets for analytics and AI workloads while ensuring governance, security, and compliance.
Design and maintain secure, scalable Microsoft Azure cloud infrastructure for enterprise applications and data platforms using IaC, CI/CD, and Azure-native services.
Designs and implements cloud-native data architectures for an insurance-focused company using Azure services like Synapse, Databricks, and Power BI to enable analytics, automation, and regulatory compliance.
Lead the rebuild of MiWay’s data warehouse and migrate it to a cloud-native platform, designing scalable ELT pipelines, medallion architecture, and robust data governance for insurance analytics.
Build and maintain secure, scalable ETL pipelines and data warehouses for a multi-tenant fintech platform using Python, SQL, Azure Synapse, and PostgreSQL.
Designs and builds scalable Azure-based data pipelines and cloud-native solutions for a bank, using ADF, Databricks, Synapse, and APIs to enable analytics and AI.
Senior Data & ML Engineer builds automated data pipelines, a central SSOT database, and AI/ML-ready data models to support reporting, analytics, and machine learning across the business.
Principal Data Engineer builds and optimizes high-performance data pipelines for a fast-growing fintech, using Azure, Snowflake, dbt, and Airbyte to power analytics and ML at scale.
Build and operate cloud-native data platforms using Python, Spark, and AWS/GCP, designing scalable ETL/ELT pipelines and modern data warehouses.
Senior Data Scientist to design Azure data pipelines, build ML models, and implement MLOps for enterprise-scale analytics and AI solutions in a 12-month contract.
Design and build scalable data pipelines on Azure Databricks and Microsoft Fabric to ingest, process, and transform financial data for analytics and AI initiatives.
Build and scale Python applications that integrate ML models, using PySpark and Kubernetes; collaborate with data scientists to deploy end-to-end ML pipelines.
Builds systems that gather, store, and process large volumes of data for analysis. Responsibilities: Develop ETL pipelines, ensure data quality, optimize data storage solutions. Skills: Python, SQL, cloud data tools…
Build and maintain scalable backend systems in .NET/C# on Azure to power H&M’s pricing and adjustment capabilities, ensuring security, performance, and reliability at scale.
Design and lead the architecture of a governed self-service data platform for a global retail enterprise using Microsoft Fabric and Azure services.
Designs and maintains scalable Azure data pipelines using Data Factory, Databricks, and Synapse to enable ETL/ELT workflows, data quality, and automation.
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