Job Description

• To understand the various data sources, how the data flows through the organization and provide expertise and support through translating business needs into tangible solutions by analyzing data, conducting root cause analysis, and recommending improvements to data pipelines, data quality, metadata, master and reference data, data access management.
• Understand data sources and map to target systems/ solutions.
• Provide transformation rules to Data Engineers.
• Understand business rules and requirements to solve specific use cases.
• Ensure that process conforms to business objectives and complies with Group Information Architecture.
• Apply company, business, Group and/ or relevant industry knowledge for analysis.
• Prepare and present findings on data analysis in written and verbal reports to key stakeholders.
• Assist with the mapping of the various source systems to the relevant enterprise data model elements (engage with the Data Modelers where the models need to be extended), and enterprise reference data.
• Query and connect data from disparate sources to identify areas where changes are required.
• Conduct analysis, time-series analysis, and classification models and deliver accurate and high-quality analysis (e.g. test design and analysis).
• Utilize methodologies and methods for accessing, analyzing and presenting data.
• Research new data sources and analytical tools with the aim of improving the process and underlying data analysis Understand the quality of data and engage with relevant stakeholders to correct data (if and when necessary), thereby ensuring usability is in line with requirements.
• Keep up to date with new data assets and products in order to identify new opportunities, capabilities and trends that would add value to business.
• Check accuracy of data and if it is within relevant thresholds (reasonability) and compare the new output with existing requirements.
• Analyse and recommend changes to data pipelines of existing and new initiatives with the aim of aligning these to avoid duplication in data pipelines, inconsistent mappings, etc.
• Partner with stakeholders to grasp problem specifics – collects, processes and analyses data to quantify the scope, nature and severity of the problem.
• Engage with Data teams to understand the data landscape.
• Engage and drive conversations with relevant stakeholders to unpack project and requirements.
• Evaluate options based on business requirements and provide input into viable solution based on analysis.
• Work with the relevant Data stakeholders when new data or changes to existing solutions are required and manage timelines and expectations with business.
• Identify opportunities/changes which need to apply in Data Analytics solutions (e.g., Cubes/Production reports).
• Attend relevant priority session and provide motivation to get item prioritized.
• Ensure proper handover and provide relevant artifacts to stakeholders.