SUMMARY:

• Innovative, visionary backed by experience track records in leveraging technologies toward accomplishing strategic and tactical business objectives, enhancing organizations resources in implementing major expense - reducing, revenue-enhancing, competitive and business flexibility improvements.
• Performance-driven with 12+ years of IT expertise in designing and implementing cutting-edge industry standards Enterprise Data Management Services Data Governance, Data Quality Management, Data Warehousing, Data Integrations, Business Intelligence, Customer Relationship Management and Enterprise Resource Planning.
• Significant experience in IT applications and data processing with Healthcare, Financial and Insurance services and Automotive industry for 15+ projects through all phases of the software development life cycle (SDLC) including requirements analysis, design, configuration, integration, testing, deployment, and maintenance.
• Strong hand on experience of modern architecture and legacy technologies, exceptional analytical skill, l earning agility and effective communication skills, self-motivated and determined, success oriented and natural leader as well as excellent team player, trustworthy and hardworking.

HIGHLIGHTS:

• Data Governance
• Data Quality Management
• Data Warehousing
• Data Integrations
• Business Intelligence
• Data Modeling
• Project Management
• Application Development

• Regulatory Compliances:
• CCAR
• DFS 504
• Operationalization Knowledge of GDPR

TECHNICAL SKILLS:

Data Quality: IBM InfoSphere suite; Information Analyzer 11.x, Discovery Studio 4.x, Data Quality Console, SAS DATAFLUX Data Management Studio 4.2, INFORMATICA Data Explorer 9.6, Data Quality 9.6, Developer. MSSQL Data Quality Services.

Data Governance: IBM InfoSphere Governance Catalog 11.x, InfoSphere Business Glossary 9.1x, Blue Print Director 2.2.0

Data Integration: INFORMATICA Power Center 9.5, IBM InfoSphere Data Stage 11.x, Quality Stage

Business Intelligence: COGNOS Report Studi0 10x, Tableau, MS PowerBI, Business Objects Cloud; Azure SQL Database, Azure Data Factory

Database: DB2, UDB, Oracle, Dbase IV, MS Access, MySQL 5x, TERADATA, MSSQL Serve 2017.

ERP: SAP BI 7.0, BW 3x SD, ECC6.0.

Languages: COBOL, CICS, JCL, C, SQL, PL/SQL, JavaScript, HTML, DHTML, CSS, JAVA, XML XSL. Python.

Software: SPUFI, QMF, File-Aid, SCLM change control, MQ Series, IBM Debugger, XPEDITOR, sync sort, SQL Developer, TOAD, HP Quality Center 9.2, MS Office suite 2013, IBM Data Studio 3.2.x, JDA, XPC (Xpress Commerce) Actimize.

Systems: MVS/ESA, Z/OS, OS/390, TSO/ISPF, JES2 & JES3, Windows 7, MS DOS, UNIX, Linux.

EXPERIENCE:

Data Solution Architect & Data Governance and Data Quality Architect

Confidential, New York, NY

Responsibilities:

• Provide vision and leadership to define the core technologies necessary to meet business needs including: development tools and methodologies, package solutions, systems architecture, security techniques, and emerging technologies.
• Develop, maintain and evangelize data architecture guiding principles, policies, best practices, architecture and standards.
• Collaborate in the building and maintaining of an enterprise data model.
• Develop and implement an effective data governance program composed of data governance policy and procedures.
• Integrate the data governance program into existing system workflow, provide analytical metrics that proves clear value in the planned approach; clearly stating each component’s purposefulness.
• Provide documentation though the creation of a business glossary and data dictionary with business rules.
• Formulate data models depicting relationships and business rules, Create and document data algorithms used in enforcing complex business rules.
• Implement a data review and change management process.
• Work with business to develop conceptual data model
• Communicate effectively across all levels of the organization to drive progress and keep leadership and all business stakeholders informed of program updates and status.
• Catalog, track and ensure remediation for known data quality issues within the Management Information Systems.
• Advance skills with spreadsheets, project management and presentation software, including a strong working knowledge of MS Excel, MS PowerPoint, MS Project and MS Visio.

Environment: MS SQL Server 2014, MSSQL Management studio 2017, MSSQL Server Integration Services, R scripts, Power BI, Azure Data Catalog, Azure SQL database, Data Factory.

Data Quality Architect /Data Analyst

Confidential, New York

Responsibilities:

• Lead Data Quality Architect DFS 504 Data Quality framework to meet industry best practices and standards, process flow, architectural roadmap at enterprise level.
• Leverage data management knowledge to maintain and define data quality and metadata processes, participate in development of data quality rules, establish attribute level threshold based on the criticality and standards metric/quality-expectations for data elements that support critical business processes.
• Developed Data Quality Reporting environment to support annual DFS 504 Critical Data Elements attestation by providing “point of time” insight into DFS 504 Critical Data Element Catalog.
• Identify tasks, task sequencing, required roles and responsibilities, and estimate work effort to operationalize DFS 504 Data Quality.
• Provide estimates of staffing requirements for project execution as well as high-level estimates for DFS 504 data quality resourcing.
• Operationalize DFS 504 compliance program in compliance with Data Governance to instantiation of key data governance and control points to assure that Transaction Monitoring and Sanctions Filtering Critical Data Element data is maintained, and Data Quality monitored.
• Data Quality Implementation, which includes Issue Management and Resolution, provides implementation steps. This work stream provides an action plan that can be used to implement DQ and IMR and is also supplemented here with an approach for prioritizing domains and control points.
• Document DFS 504 Data Quality and Issue Management Resolution requirements.
• Develop DFS 504 Data Quality communication and plans.
• Operationalization of DFS 504 DQ and IMR processes, prioritize and rationalization authoritative data Source Systems prioritization was based on several factors including DFS 504 Domain Coverage: Systems that feed data for Transaction Monitoring, Real-Time Sanctions Filtering, and Static Data Sanctions Filtering were given high priority.
• Design, develop, and implementation plan to operationalize DFS 504 Data Quality Dashboard with an ability to monitored and obtains continuous visibility into the quality of data required for key business processes and can react immediately to Data Quality exceptions and issues to remediate them.
• Work collaboratively with business data stewards to establish a comprehensive data remediation to effectively remediate data anomalies.
• Catalog, track and ensure remediation for known data quality issues within the Management Information Systems.
• Advance skills with spreadsheets, project management and presentation software, including a strong working knowledge of MS Excel, MS PowerPoint, MS Project and MS Visio.

Environment: MS SQL Server 2014, MSSQL Management studio 2014, MSSQL SSDT, UNIX Shell Scripting.

Data Governance Analyst

Confidential, New York, NY

Responsibilities:

• Work with Business Process Owners and the Data Governance User Group(s) to identify, classify and define each assigned Critical Data Element (CDEs) and ensure that each element has a clear and unambiguous definition.
• SME on enterprise Treasury and Trade Solutions data domains, CCAR and Target Record Layout attributes regional or business line organization structures and product categories.
• Collaborate with functional units to identification and collection of business and technical metadata, data calculation, sourcing, and transformation rules, and establish data lineage for delivery mappings, data standards in a centralized data governance repository.
• Worked with Data Custodians, Business Process owners and IT, in execution and implementation of Citi Enterprise-wide Data Quality Standard Operation Model and Citi Data Management Policy for regulatory compliance, operational reporting is fit for purpose and socializes progress among stakeholders.
• Partner with IT to implement data standards, business rules and DQ issues and escalation procedures
• Initiate and oversee changes (i.e. creation, modification, deletion) to CDEs, recommend the prioritization and identify the impact for the key stakeholders.
• Identifying risk mitigation controls and collection evidence to support the attestation process.
• Experience gathering a documenting requirement for data-related projects, such as data warehousing, business intelligence or operational reporting.
• Conduct working groups to remediate data issues and produce metrics to support transparency into data delivery and controls in accordance with Data Management Policies and Standards.
• Experience with Regulatory data, metadata, data lineage, defining data standards and data dictionaries.
• Strong analytical and time management skills
• Excellent written and verbal communication skills and the ability to interact with variety of customers and stakeholders
• Intermediate facilitation skills with the ability to drive issues to closure
• Self-motivated and able to handle tasks with minimal supervision or questions
• Ability to deliver a high level of customer service

Environment: MS SQL Server 2014, Compass, Rules Harmony, Enterprise DQP- AbInitio based platform

Data Quality Architect /Data Analyst

Confidential, Parsippany, NJ

Responsibilities:

• Lead Data Quality Architect to establish Data Quality best practices and standards, process flow, architectural roadmap at enterprise level Data Quality framework.
• Leverage data management knowledge to maintain and define data quality and metadata processes, participate in development of data quality rules, establish attribute level threshold based on the criticality and standards metric/quality-expectations for data elements that support critical business processes.
• Identify and Articulate Critical Data Elements (CDE) related to Customer domain for Data Governance Council Presentation & Approvals.
• Participates in and lead discussions with cross-functional teams
• Document effectiveness of Data Quality controls and metadata capture and identifies improvement opportunities. Participate in development of best practice and tools based on business needs.
• Consult with Data Governance Office to establish criteria for data quality process “compliance assessment”. Understand and influence decisions around Data Quality processes, improvement of program data.
• Define rules to evaluate data quality and create effective test plans, according to Enterprise Data and Analytics data quality standards.
• Define and articulate CDE data transformation rules ensuring good data quality flows into Enterprise Data Hub, taking into consideration survivorship, Deduplications, Derivations, Data Standardizations and Merge rule are applied.
• Defined Confidential specific Data Quality Dimensions: Accuracy, completeness, integrity, consistency, uniqueness, and timeliness of data. Execute enterprise data and analytics data quality assessments.
• Advocate Data Quality best practices and standards, process flow, architectural roadmap, thresholds and tools that promote and facilitate a seamless process and act as change agent with end to end solutions.
• Design, develop, and implementation of Enterprise Data Quality Dashboard with an ability to monitored and obtains continuous visibility into the quality of data required for key business processes and can react immediately to Data Quality exceptions and issues to remediate them.
• Work collaboratively with business data stewards to establish a comprehensive data remediation to effectively remediate data anomalies.
• Catalog, track and ensure remediation for known data quality issues within the Management information Systems. Developed Remediation Progress Rate (RPR) terminology which monitors remediation progress Rate, which is it tied up to Data Quality Dimensions.
• Advance skills with spreadsheets, project management and presentation software, including a strong working knowledge of MS Excel, MS PowerPoint, MS Project and MS Visio.

Environment: MS SQL Server 2014, INFORMATICA Data Quality 9.6, INFORMATICA Developer, Power Center. AWS, S3, Redshift, IBM DB2 UDB AS/400 (iSeries), Tableau, Hue, SQL Developer, MSSQL Management studio 2014, UNIX Shell Scripting.

Data Governance & Data Quality Architect /Data Analyst

Confidential, Bridgewater, NJ

Responsibilities:

• Lead Data Governance framework and stewardship to define, approve, track and enforce conformance and communicate date strategies, polices, standards, architecture, procedures and metrics. Setup best practices around meta-data to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, reusability, and consistent definitions for common data, Collaborated Business and IT worlds to have common ground by setting up metadata management as a core foundation between technical and business glossary.
• Identify and interact with stakeholders, subject matter expert (SMEs) and data owners to establish decision rights and clarify accountability.
• Experience in working with cross functional team in authoring Business Requirements, Functional Requirements, Database Design representation, data and systems flow diagrams, participate in document reviews with business users and ability to interpret, analyze and solve business problems with information technology solutions
• Advocate Data Quality best practices and standards, process flow, architectural roadmap, DQ dimension, thresholds and tools that promote and facilitate a seamless process and act as change agent with end to end solutions.
• Provided functional and technology leadership to develop data-centric solutions which meets organizations’ information and analytics needs while ensuring adherence and appropriate uses of PVH Enterprise Data and Analytics platforms and capabilities.
• Maps out complex business processes to serve as for development of analytics solutions and advocates for business processes implication where appropriate to deliver robust and cost-effective solutions. Drive implementation and adoption of self-service analytics models and solutions. Co-ordinates work streams, activities and initiatives as needed. Ensures compliance requirements are met, oversees documentation activities and participates in compliance activities as required and partners with Application Services to execute projects and deliver capabilities
• Author and develop data analysis and visualization to design solutions and deliver effective user-centric and intuitive analysis tools and dashboards, implements capabilities in support of the PVH Supply Chain Data Governance model. Maps out complex business processes to serve as for development of analytics solutions and advocates for business processes implication where appropriate to deliver robust and cost-effective solutions.
• Tracks progress of the solution development projects and reports to the business partners on status on the delivery of features, functionality and applications.
• Architect and develop Change Control Management System.
• Ability to solve complex business problems and strong communication and presentation skills to make effective recommendations to management, good planning, organizational and decision-making.
• Advance skills with spreadsheets, project management and presentation software, including a strong working knowledge of MS Excel, MS PowerPoint, MS Project and MS Visio.

Environment: MS SQL Server 2014, MSSQL Data Quality Services (DQS), MSSQL Management studio 2014, Oracle SQL Developer, TOAD, MS SharePoint Designer 2013, MS InfoPath, Business Glossary, INFORMATICA Power Center 9x, Business Objects, DB2, Oracle, JDA, XPC, UNIX Shell Scripting.

IT Data Quality Architect /System Analyst

Confidential, Basking Ridge, NJ

Responsibilities:

• Actively participates in the organization’s reporting delivery and data governance processes, tools and programs
• Works with leadership to identify data domains and domain leads and assists in the development and delivery of appropriate across the clinical, operational and financial domains
• Works with business owners to define and establish data quality rules, definitions and strategy consistent with department and organizational strategies and goals
• Participates in the establishment of standards for measurable data quality and implements appropriate tools to monitor quality, completeness and adherence
• Works collaboratively with Data Stewards from the business, clinical and IT areas to ensure data quality and availability while identifying gaps to be remediated.
• Develops and compiles Data Governance Metrics from all domains and reports to the Data Governance Council.
• Balance short-term versus long-term actions, strategic versus tactical requirements, while continuing to move forward towards the strategic vision; participate in the road map to achieve the vision.
• Interact with Data Owner; provide framework, stewardship, governance and decision making for the management of the enterprise data quality for project development teams, business users and other stake-holders.
• Advocate Data Quality best practices and standards, process flow, architectural roadmap, thresholds and tools that promote and facilitate a seamless process and act as change agent with end to end solutions.
• Define governance and best practices around meta-data to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, reusability, and consistent definitions for common data.
• Hands on experience with Enterprise Data Quality Management Life cycle; Discovery, Profiling, Measure, Establish Rules, Monitor, Report and Remediation.
• Establishing Healthcare Industry Data Rules to monitor data quality and experience on working with large data sets, exceptional analytical, conceptual and problem-solving abilities
• Hand on experience with Data Profiling to underpin a variety of information management programs, including data quality assessment, data quality validation, metadata management, data integration and ETL, data migrations, and modernization project.
• Author and developed data analysis presentation, distribution of data quality analysis review sessions and data measures and remediation process both up and down stream.
• Developing and managing Data Quality/Data Profiling Program with organization using IBM InfoSphere suite; Information Analyzer, InfoSphere Discovery, DataStage, Quality Stage and SQL’s to evaluate complexity for the business domain for data governance and developed enterprise-level data analysis, discovery of hidden sensitive data.
• Design, develop, and implementation of Enterprise Data Quality Dashboard with an ability to monitored and obtains continuous visibility into the quality of data required for key business processes and can react immediately to Data Quality exceptions and issues to correct them.
• Advance skills with spreadsheets, project management and presentation software, including a strong working knowledge of MS Excel, MS PowerPoint, MS Project and MS Visio.

Environment: IBM InfoSphere Suite; Information Analyzer 9.1x, Discovery Studio 4.5x, Data Quality Console, Quality Stage, Data Studio 3.2.x, Business Glossary 9.1.x, Blue Print Director 2.2.0, COGNOS Report Studio, DB2, Mainframe Copybook, UNIX Shell Scripting.

Senior IT Data Quality Analyst /Data Analyst/ ETL Architect

Confidential, Iselin, NJ

Responsibilities:

• Responsible for analyzing, designing, developing strategies and technical solutions to improve the accuracy of data, redundancies, user inferences and identifying anomalies in data at column, table and cross-table level understand importance of actual quality, content and structure of data and critical business data elements require by the business domain.
• Experience in listing the critical expectations, methods for measurement, and specifying thresholds, which the business clients can associate to data governance with levels of success in their business activities, articulated specific s or milestones as success criteria allows managers to gauge individual accountability and reward .
• Engage as a Subject Matter Expert (SME) on data quality improvements. Proactively promote consistency of data quality management goals, standards, policy, procedures, tools and techniques.
• Experience working with large data sets, exceptional analytical, conceptual and problem-solving abilities. Ability to profile and validate data sets for disparate data sources.
• Responsible for developing and managing Data Quality/Data Profiling Program with organization using IBM Info Sphere suite; Information Analyzer, Info Sphere Discovery, Data Stage, Quality Stage, INFORMATICA Data Explorer, Data Quality and SQL’s to evaluate complexity for the business domain for data governance and developed enterprise-level data analysis, discovery of hidden sensitive data.
• Authored and developed presentations, distribution of data quality analysis review sessions and data quality scorecard, which conveys key accuracy and completeness, measures for different data sources, key measures and remediation process both up and down stream.
• Authored and developed data quality analysis dashboard using Tableau, which projects data anomalies and health of data quality at table, attribute level.
• Development of data control movement (ETL) between source and target using IBM Info Sphere Data Stage and automation of data stage job using Shell Scripts. Development different level of reports to evaluate the data quality enterprise level.
• Advance skills with spreadsheets, project management and presentation software, including a strong working knowledge of MS Excel, MS PowerPoint, MS Project and MS Visio.

Environment: IBM InfoSphere Suite; Information Analyzer 11.1x, Discovery Studio 4.5x, Quality Stage.