Deepti Sharma

• Provided strong leadership to enhance team productivity and morale.
• Led cross-functional teams to achieve project milestones and deliver high-quality results.
• Established strong relationships with clients and stakeholders, ensuring long-term partnerships and repeat business.
• Improved team performance by providing comprehensive training and fostering a collaborative work environment.

Working as Sr. Manager for Global Loyalty and Benefits Platform for American Express

and creating Business Glossary, Data Quality Controls, creating lineage through Manta.

• Created Business Glossaries created in Colibra tool by renaming Business Terms and Description as per Enterprise Data Governance Standards
• Working with Manta Tool for Data Lineage.
• Tagging Business Term to Physical Data Asset
• Identifying Critical Data Elements based on Data Governance Criteria and Standard
• Applying Data Quality Controls to the attributes based on the data
• Managing Dashboard for Data Quality
• Hands on experience in System Certification for Data Governance.
• Analyzing Data Quality manually using GCP queries
• Expertise in documentation of the processes, design document, mapping specs and other application related manuals to support production activities.
• Ability to work individually and in team coordinating and resolve issues with team of SME’s and stakeholders

• Self-motivated, with a strong sense of personal responsibility.
• Worked effectively in fast-paced environments.
• Skilled at working independently and collaboratively in a team environment.
• Proven ability to learn quickly and adapt to new situations.
• Adhere to principles, policies, process, and a governance framework to manage data as an asset and manage adoption.
• Develop compliance monitoring and metrics and guiding federated data management teams on policy requirements.
• Created Dashboard for Alation Data Catalog tool.
• Investigate, conduct interviews, and perform analysis related to current data lifecycle processes across multiple business data domains.
• Risk Assessment of different Business Processes based on Data Governance Principles.
• Creating data lineage and tagging between physical data element and Business Terms
• Partner with Application Owner, Technical Manager and DBA in order to understand data, doing risk assessment, creating data elements.
• Re-mastering data elements based on Data Governance Standards.
• Masking the PII data in data catalog tool i.e. Alation.
• Maintaining Data Quality based on Data Governance Standards and Policies
• Data masking is done in compliance with CCPA and GDPR to maintain the privacy of the data.
• Identifying System of Record (SOR), System of Origin (SOO), and Authorized Data Source (ADS) .
• Assigning roles and responsibilities for Alation to the users.

• Increased data accuracy by implementing thorough data validation and cleansing processes.
• Built relationships and influenced and motivated employees to drive operational improvements.
• Standardized data collection procedures across departments, ensuring consistent data quality and enabling seamless integration of new datasets.
• Streamlined reporting processes for enhanced decision-making and business insights.
• Deploy the new core banking deposit system within the MUFG ecosystem.
• Profiling of the data for 13 different source system related to deposit system
• Creating data dictionaries based on new source systems checking the lineage of data into the new system.
• Remastering data elements in Metacenter by analyzing Key Data Elements for data dictionaries and creating Business Glossary
• Maintaining Privacy data in compliance with CCPA and GDPR.
• Transforming from legacy system to new Financial Information System.
• Design, implement and manage continuous integration and deployment within hybrid cloud infrastructures for rapid software release
• Analyze trade-offs between potential engineering solutions, selecting the optimal path and ultimately guiding the team
• Evaluate and manage security risks in solution design and implementation
• Serve as a key member of the core banking transformation technology leadership team
• Partner with business, program management, architecture, system owner, 3rd party vendors, testing and other teams as necessary to ensure successful delivery
• Manage onshore and offshore resources, including recruiting, mentorship and technologist development
• Identify, manage, and apply mitigation plans against risks to successful delivery.

• SME in maintaining data standards by maintaining a data dictionary, Business glossary and metadata.
• Re-mastering Data Element Names and Data Element Description as per the Enterprise Data Governance(EDG) Policy and Business Rules.
• Scheduling meeting with the Stakeholders i.e. ABO (Application Business Owner), SME's (Subject Matter Experts), TM (Technical Manager) DM (Domain Analyst) etc to create Data Dictionary.
• Analyzing if the Data Element is a Core Data, Non-Core Data or Privacy Data.
• Analyzing if the Data Element is SOO (System Of Origin) or SOR (System of Record)
• Develop an effective partnership with data domain teams and other key stakeholders to ensure appropriate support for activities.
• Recertification as per the EDG (Enterprise Governance Policy)
• Creation of DQCA (Data Quality Control Assessment) and creating Data Quality Inventory and Assessment.
• Providing appropriate controls based on Preventative or Detective Controls.
• Analyzing if the Data Element has sufficient Controls or having Control Gaps

• Analyzed quality and performance data to support operational decision-making.
• Created and revised procedures, checklists and job aids to reduce errors.
• Developed and maintained quality assurance procedure documentation.
• Provided regular updates to team leadership on quality metrics by communicating consistency problems or production deficiencies.
• Requirement gathering from Business team.
• Detailed data Analysis to prepare list of tables and columns affected by the change.
• Designing/Developing the Test cases/ Test scripts for QA process.
• Performing pre (sanity) check on source data to make sure the source is proper.
• Upon the completion of pre-check process, start the SIT.
• Logging defects in HP Quality and follow up until it get fix for which raised part of sanity check and SIT data validation.
• Ensuring the QA activity is completed on time to ensure the quality of data which is used to generate reports.
• Quality Assessment based on data dictionary and referring to data dictionary.
• Co-ordination with upstream teams, downstream teams and also with business team.
• Maintaining data integrity as a part of validating the data
• Coordination within team (including off-shore) to make sure other parallel projects are on track.