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Data Engineer - Mexico
Design and build scalable data platforms on AWS, Azure, and GCP for enterprise clients, using cloud warehouses, Spark, Kafka, and orchestration tools.
Azure Data Engineer: Build Scalable Data Pipelines
Designs and builds scalable data pipelines on Azure using SQL, Python, Spark, Databricks, and Snowflake to enable reliable data processing and analytics.
Data Engineer - SSIS & Cloud Data Pipelines Specialist
Designs and maintains SSIS and cloud data pipelines (Azure Data Factory, Airflow, AWS, Databricks) to deliver scalable analytics and trusted data solutions for client engagements.
Azure Data Engineer — Build Scalable Data Pipelines
Design and build scalable data pipelines on Azure using Data Factory, Databricks, and Spark, optimizing storage and collaborating with data scientists and stakeholders.
Hybrid Data Engineer: Build Scalable Data Pipelines
Build and optimize scalable data pipelines using PySpark, SQL, and orchestration tools to ensure reliable data for analytics and advanced models in a hybrid environment.
Lead Azure Fabric Data Engineer - Remote Position
Lead a team to design and build scalable Azure Fabric data platforms, including Lakehouse architectures, pipelines, and Power BI models, while mentoring engineers and collaborating with stakeholders.
Data Scientist Engineer - HKD 80-100K/m
Build and deploy AI/ML models and analytics pipelines on Azure to optimize data-driven decisions and business processes.
Lead Data Engineer
Lead a team to design and build scalable Azure-based data pipelines and Lakehouse architectures using Databricks, Delta Lake, and Azure Synapse to integrate enterprise data for analytics and AI insights.
Senior Consultant, Data Engineer, Finance Consulting
Build enterprise-grade data pipelines and cloud data platforms for financial clients, using ETL/ELT, SQL, Python, and cloud services like Azure/AWS to deliver insights and improve finance functions.
Azure Data Engineer - ETL/Databricks Specialist
Designs and maintains Azure-based ETL/ELT pipelines using Data Factory, Databricks, and SQL, optimizing code and collaborating with data modelers.
Data Engineer - AI 30-35K
Build and maintain data pipelines, ETL workflows, and RAG systems to power AI-driven analytics and LLM applications using Spark, Python, and cloud platforms.
Azure Data Engineer
Design and maintain Azure-based ETL/ELT pipelines using Data Factory and Databricks, optimize SQL queries, and implement CI/CD with Azure DevOps.
Data Engineering Role Hiring
Design and build Azure-based data pipelines and warehouses to integrate and secure business data for analytics and decision-making.
Data Engineer with WFH flexibility & large project exposure
Builds Azure-based data pipelines and Power BI dashboards for a large Hong Kong property group’s finance analytics platform, transforming raw data into executive reports and insights.
AI Data Analyst
Build AI agents and Power BI dashboards on Microsoft Azure for clients, bridging tech teams and executives while driving AI transformation through storytelling and demos.
Data Analyst /Data Engineer /Data Architect - Wealth Management
Design and build cloud-based data pipelines (ETL/ELT) using Azure Data Factory and Databricks to support analytics and reporting for a leading APAC securities firm.
AI Engineer - Hybrid
Build, deploy, and maintain AI/ML models and pipelines using Python, Databricks, MLflow, and Azure AI to deliver business solutions like predictive analytics and Generative AI.
AI Solutions Architect
Designs and owns scalable AI architectures for enterprise clients, blending Azure cloud solutions, Power Platform low-code tools, and agentic AI frameworks like LangGraph and RAG systems.
Data Engineer, Microsoft Fabric Data Warehouse (Project-based)
Build and maintain a Microsoft Fabric data warehouse using medallion architecture, SQL, and Power BI to ingest, transform, and model data for reliable reporting.
Enterprise Data Architect
Designs and governs enterprise-wide data architecture, canonical models, and cross-system integrations for ERP, CRM, and HRIS to ensure data integrity and analytics readiness.