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Architect enterprise-grade data and AI solutions for an insurer, designing cloud-native pipelines, Databricks lakehouses, and Agentic AI systems while aligning with insurance domains like IFRS17 and actuarial needs.
Senior Data Engineer builds scalable Azure Fabric pipelines using PySpark, SQL, and Databricks to deliver real-time data for analytics and AI workloads.
Build and maintain a governed lakehouse data platform for finance reporting, using Spark, SQL, Python and cloud services to deliver scalable data products for regulatory and management needs.
Build and maintain scalable lakehouse data pipelines for a leading insurance firm, using Spark, Python, and Delta Lake to support financial reporting, regulatory compliance, and analytics in a regulated environment.
Build and scale a modern cloud data platform (Snowflake/Databricks) to power analytics and reporting for a MAS-licensed fintech bridging fiat and digital payments.
Designs, builds, and integrates clinical software systems (LIS, EDIP, APIs) for a large Malaysian healthcare provider, focusing on HL7/FHIR interoperability, data pipelines, and API management to support digital transformation in hospitals.
Builds a new AI-powered data platform from scratch, focusing on full-stack development, data pipelines, lakehouse architecture, and AI-assisted features using React/Next.js, TypeScript, Node.js, Python, and Azure AI tools.
Senior Data Engineer building and scaling Google Cloud data pipelines and platforms to power analytics and ML for a hospitality-tech company.
Builds and maintains ETL/ELT pipelines, models data warehouses, and ensures reliable data for reporting and analytics using SQL, Python, and cloud tools.
Designs and builds ETL/ELT pipelines and data models for a scalable data warehouse and lakehouse to power analytics and reporting.
Designs and evolves a GCP-based data and AI platform, building scalable pipelines, analytical models, and DataOps processes to ensure data quality, availability, and governance.
Build and optimize scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, and Azure cloud services for enterprise clients.
Design and build scalable Azure Databricks Lakehouse data platforms using Python, SQL, and Spark; collaborate with Data Science teams on modern data architectures.
Build and maintain cloud data pipelines for a major Chilean bank, integrating AWS and Azure services to ensure reliable, high-quality data for analytics and BI.
Build and maintain a modern data platform on Google Cloud Platform using Lakehouse and Medallion architecture, creating scalable pipelines and analytics-ready datasets for business teams.
Build and maintain a federated lakehouse platform for a LatAm SaaS group, transforming siloed data into trusted, auditable domains that power real-time financial decisions across Chile, Mexico and Argentina.
Senior Data Engineer builds scalable cloud data pipelines and Lakehouse architectures using Python, SQL, PySpark, and Azure for modern data projects.
Build and optimize GCP-based data pipelines and Lakehouse architecture to transform raw data into strategic business assets using BigQuery, Dataform, and Medallion model.
Lead a team to design and build scalable data platforms using Microsoft Fabric, Databricks, and Azure, enabling enterprise analytics and governance.
Design and lead the transformation of Takealot’s data platform from batch to real-time, setting technical standards and governance for a high-scale ecommerce and logistics ecosystem.
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