Job Description :

Lead the delivery of Data Quality Application Rules, Record Count Reconciliation Reports, Tableau Data Availability and Data Quality Dashboards and Leadership Reports for assigned Data conversion objects.
o Gather business requirements and translate into Data Quality Application Rules. Review Field Mapping Documents, PepsiCo Data Standards, Conversion Design Documents, Key Decisions Documents to identify opportunities for Data Quality Rules. Ensure Global Template data standards are implemented and where needed facilitate exceptions management.
o Document detailed Data Quality Rule Requirements Design for each Data Conversion Object, Market and Source System. Maintain documentation on data quality rules and data quality application as the design and project evolves through the Agile project delivery.
o Drive the development needed for Data Quality Application Rules, Record Count Reconciliation Reports, Tableau Dashboards and Leadership Reporting with the Technical teams.
o Perform Functional Unit Test (FUT) of Data quality application to ensure data quality rules meet business requirements and Dashboards, Record Count Reconciliation and Leadership reports are accurate for reporting.
o Attend Daily Standup Meetings with the Data Team to provide status, blockers and ensure proper communication and priorities alignment for delivery during Sprints and Integration Test planning and execution.
o Conduct Data Quality Application Training Sessions with cross functional teams. Prepare/Update Training Materials and Procedures.
• Partner with the business data team to drive Weekly Data Cleansing process.
o Conduct Data quality Rules Review for Error Resolution with respective Owners (e.g.) Functional Data Teams, Business Cleansers, Value Streams etc. Assess and resolve complex issues.
o Perform root cause analysis by engaging appropriate teams and ensure timely error resolution to meet Project Milestone Data Load and Quality Targets.
o Review Dashboards Refresh Results on a weekly basis to ensure accuracy and update Data Readiness Weekly Status for Leadership reporting.
• During the Integration/Mock test cycles/Go Live prep and execution,
Attend Cutover Plan Reviews and kick off Sessions to provide feedback for updates.
o Conduct Validation Training sessions, create Manual Validation Checklist template for each conversion object. Setup SharePoint Repository Folders for documents.
o Drive E2E Execution for cleansing, preload, postload Data Quality Validations, Review Rule Exceptions for all objects and document Error Resolution Plans, Review Record Count Reconciliation and Leadership Reports and run queries to get counts if report is not available.
o Schedule cleansing, preload and postload validation results review meetings with respective data validators to review and align E2E results to obtain Business sign off.
o Create ALM Defects for all Issues including during the end to end data conversions and drive defects to closure.
• Escalate issues and risks to delivery and project timelines proactively.
• Adhere to Agile Methodology delivery with project schedules and deadlines.
Required Qualifications:
• Minimum Bachelor’s degree is required. Computer Science, Information Systems or Mathematics is preferred.
• Experience of working with/manipulating/analyzing big data sets (or systems built on significant datasets)
• Understanding of Data Quality/Data cleansing practices
• Demonstrated documentation acumen, presentation of data standards materials for reporting to project and stakeholders alignment.
• SQL skills or training
• Ability to use automated tools to assist in the data analysis/cleansing process tasks
• Ability to work collaboratively across project teams.
• Strong analytical skills
• Strong attention to detail
• Requires fluent communication skills including written, verbal, and presentation
• Demonstrated ability to effectively communicate within virtual teams
• Strong influencing, facilitating, and consulting skills in working with stakeholders at all levels in the organization and across departments

 

             

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