Design and develop modern data platforms using Microsoft Fabric, Azure Data Factory, OneLake, Dataflows, Lakehouse, Warehouse, Data Pipelines, and related Azure services.
Extensive full life-cycle expertise (requirements → design → development → testing → deployment) in modern data warehousing, including ETL/ELT development, CI/CD automation, enterprise data integration, dimensional and relational data modelling, data domain architecture, data lake analytics, Apache Iceberg tables, Control‑M scheduling, and enterprise BI solutions.
Perform ETL (Extract, Transform, Load) processes on large and complex transaction datasets to support business reporting, modelling, and analytical needs.
We are seeking a hands-on Databricks engineer with deep technical expertise in building, operating, and optimizing Lakehouse-based data and AI solutions. In this role, you will design, develop, and operationalize Delta Lakehouse architectures that deliver measurable outcomes for enterprise customers. You will own implementation activities, contribute to technical delivery leadership, and mentor engineering teams in best practices across data engineering, platform governance, and AI
Drive the implementation and optimization of centralized data repositories and data lake architectures, supporting enterprise-wide analytics and reporting.
Drive the implementation and optimization of centralized data repositories and data lake architectures, supporting enterprise-wide analytics and reporting.
Design, build and enhance enterprise data platforms, including Data Lakes, Data Warehouses, data pipelines and analytics solutions that power business decisions across the organisation.
Our data ecosystem will be migrating their products from Azure to AWS. Data Engineers needed to assist with new and current pipelines. All IT equipment are provided and it is the responsibilities of consultants to ensure the security of the organization's data and applications.
Perform ETL (Extract, Transform, Load) processes on large and complex transaction datasets to support business reporting, modelling, and analytical needs.
Collaborate with internal and external stakeholders to identify and acquire relevant data sources for AI/ML projects, leveraging on both structured and unstructured data to enrich the organization’s data assets.
Design, implement, and maintain scalable data pipelines using the Databricks Lakehouse Platform using technologies such as Apache Spark and Delta Lake.
Experienced professional with strong expertise in back-end development and data analytics. Proficient in Python, and SQL, with hands-on experience in cloud-native development on Azure and Infrastructure as Code (IaC) using Terraform Enterprise.
Perform ETL (Extract, Transform, Load) processes on large and complex transaction datasets to support business reporting, modelling, and analytical needs.