Senior Data Quality Analyst (Full Time) - Sugar Land, East Lawn at PROSPERITY BANK

Sugar Land, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Mar, 26

Salary

0.0

Posted On

12 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Quality Management, Data Governance, Data Profiling, Data Analysis, ETL, Data Integration, Data Cleansing, Data Quality Tools, Data Lineage, Metadata Management, Data Quality Framework, Data Quality Audits, Data Quality Dashboards, Root-Cause Analysis, Communication Skills

Industry

Banking

Description

External Applicants: Please apply through Prosperity Bank's Career Center at https://www.prosperitybankusa.com/Careers [https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.prosperitybankusa.com%2FCareers&data=05%7C02%7Csandra.olivarez%40prosperitybankusa.com%7C4351c6288a4f46ccbc9e08dcd40d9146%7C00eda10cf32f45b88e91257da01a8f7c%7C0%7C0%7C638618401955642480%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=yg2VkStkdrf7Of6ttN7si0bcqfep9Z6KvaukXq%2BSYpI%3D&reserved=0]. Applying through any other source may prevent Prosperity from receiving your application. Internal Applicants: If you are a current associate of Prosperity Bank, please apply through the internal Talent - Career Center in ADP. Prosperity Bank is an Equal Opportunity Employer. POSITION PURPOSE Strong experience working with SQL and performing data quality assessments by utilizing an enterprise data quality operating model. Will be dedicated to Data Governance Organization within the Enterprise Risk Management Department. Will work closely with executive management, business, and functional area partners to implement the data quality framework across the enterprise. This person will report directly to the SVP, Data Governance Officer. ESSENTIAL FUNCTIONS AND BASIC DUTIES This role is responsible for the quality and integrity of the enterprise data which involves: * Leading and owning data quality management across the Bank, and maturing a culture that embraces the value of data quality * Reviewing and ensuring accuracy and integrity of data from multiple data sources by using SQL queries, and comparing data to identify discrepancies * Comparing transformed data to original data to ensure all pertinent information is present * Collaborating with business and IT team members to resolve data discrepancies * Assisting data stewards in standing up data quality and issue management capability within their business /functional area * Operationalizing data quality management within each business or functional area * Managing communication and change management with stakeholders directly and indirectly impacted by data quality procedures * Developing KPIs and establishing an operational framework for actively managing data quality * Supporting operational requirements across large transformational projects * Identifying data gaps, measuring, and tracking improvements while working collaboratively with key business stakeholders * Challenging existing data quality processes, technologies, and systems to continuously seek opportunities for enhancement to achieve business/project objectives and drive greater efficiencies for the business PRIMARY RESPONSIBILITIES: * The key responsibility of this role is to promote data quality through a comprehensive data quality framework aligned to the organization’s overall data governance strategy, ensuring that data is accurate, reliable, complete, and fit for purpose. Primarily responsible for data profiling based on the various business rules; profiles source data and determines source data and metadata characteristics based on the requirement specific to ingestion and processing of data * Creates data quality rules based on the business rules and requirements by engaging with key stakeholders and filtering unique to data use and business decision making * Owns data quality design, develops, and delivers data quality, data profile, and metadata best practices for the enterprise * Responsible to identify and define logic to ensure that the data anomalies are detected and contained within established data quality thresholds * Identifies patterns, trends, and data inconsistencies; draws conclusions and provides recommendations in the form of remediation, corrective, and preventative actions * Responsible for analyzing various data sets to detect, resolve, and validate the life cycle of data quality issues * Implements data quality processes including conversion, parsing, analysis, standardization, and enrichment at point of entry and batch modes * Responsible for the development of data quality dashboards and data quality improvement life cycle * Performs root-cause analysis of data discrepancies across disparate systems and develops action plans to resolve data quality issues * Develops data quality dashboards and data quality improvement life cycle * Responsible for process modeling by understanding and documenting the lineage of data as it moves and is transformed through various systems * Maintains a broad knowledge of new data management technology tools and trends and applies that knowledge to architecture designs * Works collaboratively across the company to drive adoption of technical standards, design principles and architecture patterns in information management functional areas. * Monitors data quality, and analytical systems usage, and takes corrective and enhancement actions as necessary * Influences and communicates effectively with non-technical audiences including senior business management * Designs and executes data quality audits SUPERVISORY RESPONSIBILITIES: This role has no supervisory responsibilities. QUALIFICATIONS Education/Certification: Bachelor’s degree in Business, Finance, Marketing, Computer Science, or related field Required Knowledge: Familiarity with data management principles and practices in Data Management Body of Knowledge, 2nd Edition (DMBOK2) Familiarity with data management frameworks such as DCAM Knowledge of standards, and best practices prevalent in data governance, data management, data quality, and data privacy Experience Required: Minimum 7 years of experience in end-to-end data quality management, data lineage, metadata management, issue management and resolution, master data management (MDM), data integration, ETL, data warehouses, cloud technologies and repositories Extensive experience with data discovery, profiling, cleansing and standardization, data quality rules management, developing reusable data quality validation, data quality monitoring and reporting Extensive experience writing moderately complex SQL queries; hands-on data analysis of databases and files using Excel and SQL, and proficiency with programming languages such as SAS etc. Strong experience with Excel, ETL tools and related technologies Experience in designing, implementing and documenting data quality procedures, metrics, KPIs, dashboards, and thresholds Experience in providing analytic support by coordinating data extraction from various databases and data interpretation In-depth understanding of data quality management technology landscape, processes, and design principles Experience in designing, developing, and delivering data quality, data profile, and metadata best practices for the enterprise Experience with any of the data quality tools to query and manipulate data in varying file formats by using tools such as IDQ, TAMR, Infosphere, Alation or others. Experience with data governance and catalog solutions, systems integrations, and master data management solutions Experience PREFERRED: Experience with data modeling techniques, logical design, and physical design and best practices Proven experience at a premier audit or consulting firm and financial services experience is strongly preferred Experience gathering and analyzing business data requirements, including for regulatory and compliance purposes Experience in a complex regulated industry environment, with actual regulatory experience preferred Ability to successfully bring together and drive cooperation across diverse teams with potentially conflicting goals and objectives Experimental mindset to drive innovation amidst uncertainty Exposure to the following a plus: Hadoop, Teradata, Tableau Skills/Abilities: Ability to apply the principles of data quality standards and convey complex concepts to business stakeholders in terms relevant to the business Keen attention to detail and ability to identify errors, patterns, and gaps Excellent data analysis skills, knowledge of various databases, including big data technologies Proven experience in leveraging traditional technology systems as well as emerging technologies to support the sourcing/capture, governance, management, and analysis of data Convey complex technical issues/problems to developers in a clear and concise manner Strong experience with MS Office suite including Word, Excel, PowerPoint and project management software skills Ability to learn quickly, follow instructions, and work independently Ability to establish priorities, manage deadlines, exercise a high degree of professionalism in interactions with all levels of internal and external clients Monday - Friday: 8:00AM - 5:00PM 40 hours

Responsibilities

The role is responsible for leading data quality management across the bank and ensuring the integrity of enterprise data. This includes developing data quality rules, collaborating with stakeholders, and operationalizing data quality management.