Purpose The purpose of the Data Engineer is to leverage their data expertise and data related technologies technologies, in line with the Company Data Architecture Roadmap, to advance technical thought leadership for the purpose data products, and support data initiatives. In addition, Data Engineers enhance the data infrastructure infrastructure of the bank to enable advanced analytics, machine learning and artificial intelligence by providing providing clean, usable data to stakeholders. They also create data pipelines, Ingestion, provisioning
bottlenecks, reducing manual data intervention, avoiding unnecessary data capture and/or work effort duplication support. Documentation throughout all project phases, data migration strategy and execution, project go-live
support. Documentation throughout all project phases, data migration strategy and execution, project go-live bottlenecks, reducing manual data intervention, avoiding unnecessary data capture and/or work effort duplication
actionable insights and recommendations. Utilize data visualization tools to create dashboards and reports experience in business analysis, data analysis, or a related field. Proficiency in data manipulation and analysis report writing . SDLC experience Experience with data visualization tools. Strong analytical and problem-solving problem-solving skills, with the ability to translate data into actionable insights. Excellent communication
support project teams in requirements gathering, data mapping, testing, training, and post-deployment implementation in accordance with best practice processes. Data Analysis: Analysed enterprise business processes utilizing various meetings, direct observation, data analysis, document review, and questionnaires. Business Skills required Experience with managing complex data integration implementations. Experience in developing translate user stories and acceptance criteria for data-centric business needs and enterprise integration
support project teams in requirements gathering, data mapping, testing, training, and post-deployment implementation in accordance with best practice processes. Data Analysis: Analysed enterprise business processes utilizing various meetings, direct observation, data analysis, document review, and questionnaires. Business Skills required Experience with managing complex data integration implementations. Experience in developing translate user stories and acceptance criteria for data-centric business needs and enterprise integration
and approach. Attention to detail and accuracy in data entry, record-keeping, and document preparation
Microsoft Dynamics). Strong understanding of CRM data models, workflows, security models, and APIs. Experience