Data Engineer - Azure

Job Description

The successful applicant will be working within a highly specialised and growing team to enable delivery of data and advanced analytics system capability. Roles and Responsibility : - Develop and implement a reusable architecture of data pipelines to make data available for various purposes including Machine Learning (ML), Analytics and Reporting - Work collaboratively as part of team engaging with system architects, data scientists and business in a healthcare context - Define hardware, tools and software to enable the reusable framework for data sharing and ML model productionization - Work comfortably with structured and unstructured data in a variety of different programming languages such as SQL, R, python, Java etc - Understanding of distributing programming and advising data scientists on how to optimally structure program code for maximum efficiency - Build data solutions that leverage controls to ensure privacy, security, compliance and data quality - Understand meta-data management systems and orchestration architecture in the designing of ML/AI pipelines. - Deep understanding of cutting edge cloud technology and frameworks to enable Data Science - System integration skills between Business Intelligence and source transactional - Improving overall production landscape as required - Define strategies with Data Scientists to monitor models post production - Write unit tests and participate in code reviews Skill Requirement : - Expert in programming languages such as R, Python, Scala and Java - Expert database knowledge in SQL and experience with MS Azure tools such as Data Factory, Synapse Analytics, Data Lake, Databricks, Azure stream analytics and PowerBI - Modern Azure datawarehouse skills Consulting Services (Tech Talents | Contracting & Permanent) | Solution Engineering | SaaS Products (Consulting, Implementation & User-adoption) - Expert Unix/Linux admin experience including shell script development - Exposure to AI or model development - Experience working on large and complex datasets - Understanding and application of Big Data and distributed computing principles (Hadoop and MapReduce) - ML model optimization skills in a production environment - Production environment machine learning and AI - DevOps/DataOps and CI/CD experience Technical skills additional : AWS experience Qualification : Bachelor's or Master's degree in Computer Science or related field.