Daa LABS is a leading provider of innovative data solutions, helping businesses leverage data to drive strategic decisions. As part of our continued growth, we are seeking a highly skilled and motivated Data Engineer with expertise in Microsoft Azure and Databricks to join our Data Analytics team on a fixed term contract. As a Data Engineer at daa, you will be responsible for designing and implementing data solutions using Microsoft Azure and Databricks, ensuring scalable, efficient, and secure data pipelines while meeting the needs of both technical and business stakeholders. You will work closely with cross-functional teams to understand data requirements and design & develop cloud-based solutions that support real-time and batch data processing, advanced analytics, and machine learning workflows Design, develop and implement robust, scalable, and efficient data pipelines in our Azure/Databricks cloud platform, for real-time and batch workloads Implement ELT processes to integrate data from various sources into the CDP Implement data quality checks, monitoring systems, and alerts for pipeline health Manage and optimize data workloads in the data platform, ensuring performance, cost-efficiency, resiliency and security Collaborate with data scientists, analysts, and other engineers to understand data needs and deliver optimal solutions from ingestion through to visualisation Ensure data solutions comply with data governance, security, and privacy requirements Understand cloud infrastructure provisioning using Infrastructure as Code (IaC) tools e.g. Terraform Ensure data integrity, security, governance, and compliance in all data solutions, adhering to industry best practices and regulations Mentor and guide junior data engineers leveraging industry wide best practices and technical excellence Troubleshoot and resolve data-related issues, ensuring data accuracy and performant pipelines Stay current with the latest technologies and trends in cloud computing & data engineering particularly within the Microsoft Azure and Databricks ecosystems Require Qualifications? 5+ years of experience in data engineering with at least 3 years in Azure Cloud Technical Skills: Strong experience in Microsoft Azure, including Azure Data Factory, Azure SQL Database, Azure Storage, Azure Key Vault, Function & Logic Apps, Cost Analysis and other related Azure cloud services Experience with Databricks, including data engineering, data processing, and analytics development Strong understanding of performance optimisation best practices & data governance frameworks (e.g Databricks Unity Catalog) Strong knowledge of ETL/ELT processes, data modelling, data warehousing concepts and medallion architecture Experience with real-time data processing frameworks (e.g., Apache Kafka) Proficiency in Python programming language Expertise in PySpark, SQL and experience working with large-scale datasets Knowledge of CI/CD DevOps practices and tools (Git, Azure DevOps) Experience working with Agile methods of delivery Cloud infrastructure provisioning using Terraform Infrastructure as Code (IaC), desirable Knowledge of machine learning integration with ML Ops desirable Soft Skills: Excellent problem-solving and analytical skills Strong communication skills and the ability to collaborate with business and technical teams Ability to manage multiple tasks in a fast-paced environment Excellent leadership, & mentoring of junior team members Solid understanding of data governance, security protocols, and compliance standards Committed to daa values.