SUMMARY

• An inspiring leader who is passionate about using technology and data to solve Enterprise - scale problems, to deliver world-class data content to decision makers and customers via high-impact end-to-end data management strategies and data policies.
• Leads by example, hands-on experience, reflected in continuous process improvement and application of visionary change to data quality practices through cutting-edge (big) data solutions, cloud computing and open source frameworks.
• Manages institutional growth through perceptive analysis of technology trends and organizational capability and capacity.
• Pharmaceutical background to adopt practices that ensure regulatory compliance solutions for accurate reporting around risk exposure and capital management.
• Broad experience data deliveries (data cleansing, data integration, data standardization) and data quality automation, as well as in cross-functional teams that drive organizations to exponential financial success

TECHNICAL SKILLS

Project Management & planning: MS Project, Excel, PowerPoint

BUSINESS SUPPORT knowledge: Knowledge of accounting (IFRS), finance (CCAR) (Passed CFA L2), insurance/ banking products, business operations, legal/ compliance, audit/ risk management

Data ETL (Extract, Transform, Load): Informatica, SAS DMS, Erwin Modeler/ Navigator (master) data INTEGRATION, metadata governance, Cleansing, Standardization, enrichment, & remediation, automation SAS Data Management Studio, Informatica MDM Architect, Pearl (Regular Expression), Waterline, IBM Information Analyzer, IBM Data Stage, IBM Director

System Quality Assurance: Mercury Quality Center, HP Quality Center, HP Application Lifecycle Management (HP ALM) 11, Winrunner

Business Intelligence & Analytics: IBM Cognos, SAS BI, SQL, Qlikview, Tableau, Google Analytics, Microsoft SQL Server Reporting Service

Data mining, Querying & Reporting: Aqua Studio 12, SQL Navigator, Toad

Requirement Gathering: Caliber RM, MS Word, HP ALM

Other Programming Languages: Java, HTML5, CCS, C++, C#, JavaScript, python, py2neo

Database/ big data: NoSQL (Neo4j, Hadoop/HBase, Amazon SimpleDB, Cloudera, Cloudata, MongoDB, Azure DocumentDB, IBM Informix), Microsoft SQL Server, Oracle, Access, mySQL, IBM DB2, Teradata, Netezza

Technology Leadership Benchmarks & Career Progression: Program Manager (AIG) - Data Quality Team Leader, VP (Citizens Bank/CFG Financial Group) - Data Manager (Techcombank) - Data Quality Strategist (BMS) - Business Analyst (CCH/Wolterskluwer)

PROFESSIONAL EXPERIENCE

Confidential

PROGRAM MANAGER

Responsibilities:

• Oversaw program development and execution including project resourcing, budgeting, stakeholder/communication plans, issue management resolution (IMR) plans, user acceptance testing, requirement gathering and implementation plans.
• Acted as a dedicated business liaison between data owners and the technology team, to gather desired application capabilities, identify minimum viable products (MVPs), prioritize features, discuss and decide alternatives and trade-offs.
• Worked with and across Agile teams to develop the overall data management metrics and reporting content to stakeholders.
• Performed functional lineage analysis to identify, access framework gaps and proposed remediation plan to close them.
• Partnered with IT to mitigate frequent bottleneck areas and work duplications to help define best practices and enhance work flows as they were integrated into BAU processes over time.
• Supported technical solutions with data life cycle management (DLM) across a full-stack of development tools/ technologies, systems development life cycle (SDLC).
• Established and provide program guidance to Data Solutions key business partners throughout the data life cycle
• Established a formal metadata management and data governance program that translate enterprise data value proposition into tangible operational value.
• Partnered with business management team to develop firmwide program awareness, knowledge training/ workshops to cultivate business relationships

Confidential

DATA QUALITY TEAM LEADER

Responsibilities:

• Acted as a dedicated business partner for data owners to participate in the Enterprise Information Management Program to prioritize, drive and monitor the integration of data, plan and act on improvement/ correction opportunities
• Oversaw project proposals, led program planning and engagement activities, identified major uncertainties in program planning and provided insights that yielded efficient resource management.
• Led delivery support activities in areas of data quality standards, data governance, and data management including CFG data management policies.
• Established metadata management and data governance practices that promoted efficient inventory of data input controls and related documentation, audit trails.
• Oversaw program implementation including project resourcing, budgeting, issue management resolution (IMR) plans, communication plans, user acceptance testing strategies and plans.
• Established well-governed data analysis and monitoring processes, emphasizing Data Quality Automation for data remediation and management.
• Led the effort to mitigate risks associated with staff turn-over by improving transparency across the organization for knowledge sharing, knowledge transfer.
• Oversaw tool capability and utility to maximize ROI of existing technology
• Performed business analysis to identify areas for reusability, parallel execution, and automation
• Established auditing processes to eliminate work and tool duplications and leveraging past deliverables for future activities.
• Defined and led reporting activities for data quality management across projects within the program

Confidential

DATA MANAGER

Responsibilities:

• Established and oversaw Data Quality Management program and aligned it with existing and new business processes.
• Acted as a dedicated business partner for owners of data inside and outside of the bank to win over data program commitment and engagement.
• Assessed the business environment, and interpreted complex data gathered from various sources to produce insights that helped achieve data governance objectives.
• Led the effort to identify areas whose costs could be cut with the deployment of new technology and staff selection while keeping the bank’s top performance momentum.
• Provided Data Quality management guidance to key partners in data profiling, data sourcing, data mapping, lineage establishment and maintenance.
• Defined data stewardship, data governance roles and responsibilities, metadata management process, metadata scorecard metrics, and metadata gathering process.
• Led data profiling, and quality assessment groups and collaboration efforts.

Confidential

DATA QUALITY STRATEGIST

Responsibilities:

• Identified the company’s strengths and weaknesses and suggest areas of improvement
• Motivated and committed to succeed in tightly knit/globally distributed teams to meet tight deadlines from functionally demanding clients
• Authored data profiling standards to establish best practices of data profiling and data quality assessment.
• Analyzed business data using top-down logical data modeling for integration and consistency and bottom-up source data analysis for standardization and quality techniques
• Participated in evaluating new software compatibility issue, design and implemented a positive solution
• Performed impact analysis on all source data to determine its completeness and accuracy before retirement or enrichment decision to facilitate project road map
• Created and maintained cleansing rules to dedup and select best-of-breed, merge data at cell value with Dataflux, Trust Framework (trust algorithms) and eliminate corrupted records
• Handled trust and survivorship rules to maintain FDA regulatory compliance and requirements
• Assisted in the synchronization of best-of-breed data to other business warehouse/ intelligence (BW/BI) systems, ensuring data is reused and shared across enterprises.
• Authored data quality monitoring scorecard to measure the quality of potential data sources against established data requirement
• Worked closely with Senior Management to gather data quality reporting requirements, designed and managed reports and report management.
• Defined process to gather metadata and lineage information across multiple sources of product data.
• Designed data lineage maintenance process and supplemental data quality artifacts including data dictionaries, data mapping, and data models.