Conduct a thorough assessment of existing data sources to identify data quality issues, inconsistencies, and gaps. Profile data to understand its structure, relationships, and dependencies.Data Mapping and Transformation: Collaborate with stakeholders to define data mapping rules from source to target systems. Develop and implement data transformation processes to ensure compatibility between systems.Quality Assurance: Implement data quality checks and validation procedures to ensure the accuracy and completeness of migrated data. Investigate and resolve data quality issues, working closely with the data engineering team.Documentation: Create comprehensive documentation for data migration processes, including data dictionaries, mapping documents, and transformation rules. Maintain clear and detailed records of data quality assessments and issue resolutions. Work closely with data engineers, business analysts, and other stakeholders to understand business requirements and ensure data migration aligns with organizational goals. Collaborate with IT teams to optimize data migration processes and troubleshoot technical issues.Reporting and Monitoring: Develop and implement reporting mechanisms to track the progress of data migration activities. Monitor key performance indicators (KPIs) to ensure the project stays on track.Data Governance: Ensure adherence to data governance policies and best practices throughout the data migration process. Contribute to the development and improvement of data governance frameworks. Identify potential risks and challenges related to data migration and propose mitigating strategies. Proactively communicate risks to project stakeholders.As a Data Analyst, you will be expected to create various documentation deliverables to communicate your analysis, findings, and recommendations effectively.Data Requirements Document: This document outlines the data needs for a specific analysis or project. It describes the data sources, variables, formats, and any specific data transformations or cleaning required.Data Dictionary: A data dictionary provides a comprehensive description of the data elements used in the analysis, including definitions, data types, and any relevant metadata. It helps ensure a common understanding of the data among stakeholders.Data Cleaning Documentation: This documentation details the steps taken to clean and pre-process the data, including any data transformation, handling of missing values, and outlier treatment. It ensures transparency and replicability of the data cleaning process.Data Analysis Plan: The data analysis plan outlines the specific analysis techniques, models, and statistical methods to be used to address the research questions or objectives. It defines the variables to be analyzed and the sequence of steps to be followed in the analysis. Analysis ResultsSummary: This document provides a concise summary of the key findings and insights derived from the data analysis. It highlights the main trends, patterns, correlations, and any significant observations discovered during the analysis.Data Visualization Reports/Dashboards: These reports or dashboards present visual representations of the data analysis results. They include charts, graphs, and other visualizations that effectively communicate the findings to stakeholders in a clear and intuitive manner.Recommendations and Actionable Insights: This document outlines the actionable recommendations based on the data analysis results. It provides insights and suggestions for decision-making, highlighting areas of improvement, potential risks, and opportunities.Methodology and Assumptions: This documentation describes the analytical methods, models, and assumptions used in the analysis. It helps stakeholders understand the rigor and validity of the analysis and enables reproducibility.Project Documentation: Depending on the scope of the project, you may need to maintain project documentation that includes project plans, timelines, milestones, and any relevant project management artifacts.User Guides and Training Materials: If your analysis involves the development of data products or tools, you may need to create user guides and training materials to help stakeholders understand and utilize the outputs effectively. OTHER Undertake any other duties requested by the Lead.EXPERIENCE AND QUALIFICATIONBachelor’s degree in computer science, Information Systems, or a related field.A master’s degree is a plus. Proven experience as a Data Analyst with a focus on data migration projects (2-3years). Strong proficiency in SQL and scripting languages for data manipulation and analysis. Experience with data profiling tools, ETL processes, and data quality management. Familiarity with data visualization tools. Excellent problem-solving skills and attention to detail. Strong communication and interpersonal skills for effective collaboration. Ability to work independently and as part of a cross-functional team. Understanding of data governance principles and best practices.Knowledge of industry Standard data migration methodologies.#J-18808-Ljbffr