We provide IT Staff Augmentation Services!

Data Quality Analyst Resume

SUMMARY

  • 6+ years of experience as a Business Analyst in Finance industry within Agile and Data Governance Space.
  • Experienced in gathering requirements for application development projects involving Agile Scrum and Waterfall methodologies and created Use Case Models, Data Flow Diagrams (DFD) and Activity Diagrams.
  • In - depth knowledge of Software Development Life Cycle (SDLC) methodologies like Waterfall & Agile.
  • Proficient in designing workflows and elaborating them with respect to change management principles; Business Process Mapping and Business Process Re-engineering utilization in mapping, modeling and structuring of the Enterprise Business Process Hierarchy.
  • Highly proficient in technical and business writing, business process flow, business analysis and testing various methodologies.
  • Strong understanding of project life cycle and SDLC methodologies including agile- scrum/safe.
  • Competent in creating unified modeling language (UML) diagrams such as use case diagrams, activity diagrams, class diagrams and sequence diagrams.
  • Experienced in working with the key components of the Collibra DGC such as Business Glossary, Reference Data Stewardship, Data Dictionary, Data Helpdesk, Policy Manager, Issue Management, Catalog, etc.
  • Strong knowledge in Data Quality, Data Profiling, Scorecards, Data Quality Metrics, Metadata Management.
  • Expertise with Informatica Data Quality (IDQ) toolkit, data cleansing, data matching, data conversion, data profiling, exception management, reporting and monitoring functions.
  • Strong experience in Integration using Mule ESB in integrating various third party solutions.
  • Proficient in performing checks for data completeness, accuracy, transformation and quality to reconcile the data.
  • Well versed in test planning, test preparation, test execution, issue resolution and report generation to assure that all aspects of a project are in compliance with the business requirements.
  • Strong experience in conducting User Acceptance Testing (UAT), documentation of test cases, test plans and test scripts.

TECHNICAL SKILLS

Modeling Tools: Enterprise Architect, MS Visio, Smart Draw

User Interface Modeling: Balsamiq, SnagIt, Moqups.com, Axure RP

Requirements Management Tools: JIRA, Rational DOORS, RALLY, Team Foundation Server, Confluence

Testing Management Tools: Bugzilla, JIRA, Quality Center, QTP

Methodologies: Agile, Waterfall, Hybrid SDLC, Scrum

Enterprise Data Management: Collibra, Informatica, Abinitio, IBM Information Analyzer, IBM IGC

PROFESSIONAL EXPERIENCE

Confidential

Data Quality Analyst

Responsibilities:

  • Support metadata repository maintenance, access requests, and proper metadata association
  • Review, validate, and record metadata and data quality information
  • Development of definitions, data quality rules, thresholds, and standard metrics of quality for data elements that support critical business processes
  • Development of controls to mitigate data quality risks including data quality plan development, monitoring data quality results, reports and dashboards, as appropriate
  • Identify and maintain data quality corrective action plans
  • Support compliance assessment process by reviewing and documenting failures from data quality compliance assessment checks
  • Recommend Master and Reference Data processes and procedures to align with Enterprise Policies and Standards
  • Create and maintain reference data in accordance to defined processes and procedures.
  • Responsible for developing data definitions, data quality rules, data asset management, establishing thresholds, reports and dashboards

Confidential

Senior Data Steward

Responsibilities:

  • Participated in the Data Stewardship function across the enterprise to uncover the definitions, ownership, and key characteristics of enterprise data.
  • Verified the business definitions of data and determined its context, sourcing and use. Performed quality checks on the information provided to make sure it meets standards defined by the program.
  • Developed and maintained data flow lineage for various applications under review.
  • Assisted in setting formal standards, policies and processes regarding data stewardship, governance and management.
  • Informed business teams of the behavior that is leading to quality issues and collaborate to raise the awareness of the impacts on the organization.
  • Ensured that data is normalized within the system.
  • Created SQL queries in IBM Infosphere Server Console to make sure that the data within the application is compliant to the data rules provided.
  • Ran the data rule queries to provide the business teams with updated exception sets in Data Quality Exception Console for the applications.
  • Maintained periodic monthly integrity checks for all the terms across all the applications for regulatory compliance purposes.

Confidential

Data Governance Analyst/ Collibra Consultant

Responsibilities:

  • Managed the strategy and vision of the Enterprise Data Management to support the Data Governance program.
  • Assisted the Data Governance Manager with the formation of a new data documentation process that improved data usage, quality for the entire organization.
  • Developed and maintained ETL (Extract, Transformation and Loading) mappings to extract the data from multiple source systems like Oracle, SQL server and Flat files and loaded into Collibra.
  • Used IDQ to profile the project source data, define or confirm the definition of the metadata, cleanse and accuracy check the project data, check for duplicate or redundant records, and provide information on how to proceed with ETL processes.
  • Created Communities, Domains and Assets within Collibra.
  • Built the code values, code lists, attributes in Collibra DGC.
  • Designed and managed process workflow to identify, classify and define critical data elements that mitigated risk.
  • Integrated the Abinitio Metadata Hub with the Collibra Data Governance Center.
  • Expedited root cause analysis for the Data Governance Team by assuring the authentication of metadata, detailed reports and priorities of data quality issues among various lines of work.
  • Utilized Informatica Data Quality(IDQ) to determine the data quality issues for the MDM data.
  • Identified critical data element failures used for reporting and analysis across credit, financial analytics, regulatory and operational reporting.
  • Defined the business glossary, rules, processes and metrics that identify gaps and ensured compliance with standards across the enterprise data stewardship.
  • Implemented data lineage and controls working with project and business leaders to analyze the impact of future changes on critical data elements and mitigated any potential risks to data quality.
  • Designed and developed several flows for new requirements and variety use cases using the MuleSoft Anypoint Studio of Mule ESB
  • Developed the integration workflows using a MuleSoft ESB 3.7.3 framework.
  • Performed cost-benefit and return-on-investment analysis for proposed systems to aid management in making implementation decisions.
  • Interpreted data, analyzed results using statistical techniques and provided ongoing reports.
  • Conduct risk assessments and effectively review policy and procedure controls to ensure compliance; generate reports and review results, risks, and developed remediation of any compliance risks with LOB management.
  • Compiled regulatory reports with securities processing for internal central reporting teams and regulatory agencies.
  • Developed and implemented databases, data collection system, data analytics, and other approaches to optimize statistical efficacy.

Confidential

Business Systems Analyst/Data Governance Analyst

Responsibilities:

  • Worked with business partners to identify critical data elements for the projects in scope. Performed initial analysis and partnered with MIS and Business teams to define and capture metadata, lineage, business rules and transformation logic.
  • Owned end-to-end governance process within Collibra across all the identified domain. Analyzed root cause for issues identified and engaged the right parties across the teams for timely resolution.
  • Set up Collibra Communities, Domains, Types, Attributes, Status, Articulation, Workflow and customize attribution and solution including custom dashboard with metrics, status, workflow initiation and issue management for each Domain specific requirements.
  • Integrated IDQ Mappings and Mapplets with Collibra and scheduled jobs to run the workflows.
  • Managed integration of Collibra Connect with various 3rd-party sources using Mulesoft ESB.
  • Defined Business rules in Informatica Data Quality (IDQ) to evaluate data quality by creating cleanse processes to monitor compliance with standards and assist in resolving data quality issues.
  • Worked with IT to establish processes for an on-going maintenance and set up exception reporting and metadata changes.
  • Consulted with stakeholders to identify the requirements to build data lineage for existing processes.
  • Managed workflow process in Collibra.
  • Responsible to work with the business for RACI activities and incorporate them within Collibra.
  • Developed key relationships with SME’s and data owners and driven discussions to standardize attributes & metrics and assisted with establishing clear ownership of data elements.
  • Assisted Data Quality team with establishing data quality rules, thresholds, quality reports & dashboards.
  • Collaborated with reporting analysis and data strategy functions to represent needs of the domain, assessed and identified impacts across multiple projects.
  • Contributed to the development of training materials and coached small groups on the new processes across the data governance lifecycle.
  • Created MULE ESB artifact and configured the MULE configurations files and deployed.
  • Developed ETL mapping Documents for every mapping and Data Migration document for smooth transfer of project from development to testing environment and then to production environment.
  • Escalated project timeline and quality issues appropriately to ensure overall program success.
  • Supported the development and implementation of new data policies.
  • Supported the creation of program business definitions and data management goals and principles for execution.
  • Compiled regulatory reports with securities processing for internal central reporting teams and regulatory agencies.
  • Optimized and redefined procedures to improve efficiency and reduce regulatory breaks.
  • Performed data analysis for various enterprise wide data quality initiatives.
  • Coordinated the analysis of data gaps by collaborating with appropriate data owners and business partners.

Hire Now