Senior Manager, Data Analytics

802 Respect Dr
Bentonville, AR

R-2632999

$90,000 - $180,000/yr

Regular/ Permanent

Data Source Identification Requires knowledge of Functional business domain and scenarios Categories of data and where it is held Business data requirements Database technologies and distributed data stores eg SQL No

SQL Data Quality Existing business systems and processes including the key drivers and measures of success To support the understanding of the priority order of requirements and service level agreements Help identify the most suitable source for data that is fit for purpose Perform initial data quality checks on extracted data

Tech Problem Formulation Requires knowledge of Analyticsbig data analytics automation techniques and methods Business understanding Precedence and use cases Business requirements and insights To translate coown business problems within ones discipline to data related or mathematical solutions Identify appropriate methodstools to be leveraged to provide a solution for the problem Share use cases and gives examples to demonstrate how the method would solve the business problem

Data Visualization Requires knowledge of Visualization guidelines and best practices for complex data types Multiple data visualization tools for example Python R libraries GGplot Matplotlib Ploty Tableau PowerBI etc Advanced visualization techniques tools Multiple story plots and structures OABCDE Communication influencing technique Emotional intelligence To identify and recommend the most suitable visualization tools based on context Generate appropriate graphical representations of data and model outcomes Understand customer requirements to design appropriate data representation for complex data sets and drive User Experience designers and User Interface engineers to build front end applications Define application design based on customer requirements Build compelling stories based on context to integrate multiple pieces of information into cohesive insights Present to and influence audiences using the appropriate data visualization frameworks and conveys clear messages through deep business and stakeholder understanding Customize communication style based on stakeholders and leverages relationships to drive behavioral change Guide and mentor junior associates on story types structures and techniques based on context

Data Strategy Requires knowledge of understanding of business value and relevance of data and data enabled insights decisions Appropriate application and understanding of data ecosystem including Data Management Data Quality Standards and Data Governance Accessibility Storage and Scalability etc Understanding of the methods and applications that unlock the monetary value of data assets To Understand articulate interpret and apply the principles of the defined strategy to unique moderately complex business problems that may span one or main functions or domains

Data Quality Management Requires knowledge of Data quality management techniques and standards Business metadata definitions and content data definitions Data profiling tools data cleansing tools data integration tools and issues and event management tools Understanding of users data consumption data needs and business implications Data modeling storage integration and warehousing Data quality framework and metrics User access best practices Enterprise data architecture modeling and design storage integration and warehousing Enterprise data quality framework and metrics Enterprise data strategy Enterprise data quality strategy Enterprise strategy to address regulatory and ethical requirements and policies around data privacy security storage retention and documentation To promote and educate others on data quality awareness Profile analyze and assess data quality Test and validate data quality requirements Continuously measure and monitor data quality Deliver against data quality service level agreements Manage operational Data Quality Management procedures Manage data quality issues and leads data cleansing activities to remove data quality defects improve data quality and eliminate unused data Determine user accessibility and removes or restricts user access as needed Interpret company and regulatory policies on data Educate others on data governance processes practices policies and guidelines

Understanding Business Context Requires knowledge of Industry and environmental factors Common business vernacular Business practices…