• $131,430.00 -199,650.00/year*
  • Jersey City , NJ
  • Executive Management
  • Full-Time
  • 164 Van Horne St

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Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), the 5th largest financial group in the world (as ranked by SP Global, April 2018) with total assets of over 2.9 trillion (106.2 (JPY) as of March 30, 2018) and 150,000 colleagues in more than 50 countries. In the U.S., we're 13,000 strong, working together to positively impact every customer, organization, and community we serve. We achieve this by delivering on our values, putting people first, fostering long-term relationships built on honesty and mutual understanding, and inspiring the best in each other. This is all part of our inclusive, high-performing culture supported by Total Rewards that include our cash balance pension plan. Join a team that's working to fulfill its vision to be the world's most trusted financial group. Data Quality Controls Engineer Assistant Vice President Job Summary Senior Data Quality Controls Engineer developer with a strong working experience in Data Governance projects in Financial Services Industry. The ideal candidate will work with SMEs in Chief Data Office Organization, Data Warehouse, and in LOBs to understand the data quality monitoring requirements for key data elements across various productsdata domains. Implement Enterprise Data Governance and Data Quality Solutions both in current state and future state data platforms to achieve the intended outcomes while following the banks processes, standards, and procedures. Implement re-usable frameworks for Reconciliations and controls and ensure consistency across domainslayers. Lead Data Quality and Controls projects as assigned. Assist the management with capturing metrics for DQ measurement points and golden sources and present the metrics in a data quality metrics dashboard. Contribute to the organization's efforts for Enterprise Data Quality Problem Management process and documentcreate a DQ Playbook as part of establishing DQ operating model. Major Responsibilities Understand Data Governance Framework consisting of Business Information Model, Metadata Management Framework, Golden Sources Management, Integrated Controls Framework, and Data Quality Problem Management Processes. Analyze the KDEs for reports or consumption processes submitted by LOBs or Consumers. Work with the Domain Working Groups to understand KDE mapping to BIM (Business Information Model) Domains and Sub Domains. Identify Data Quality Control Points for source data extraction and ingest data into DQ staging through ETL Query and profile data. Prepare Source to Target data mapping documentation for developers Understand DQ dimensions applicable for each KDE (Key Data Element). Define data quality checks (existence, consistency, defaults, cross field) and cleansing rules Develop DQ rules in Informatica Data Quality. Analyze DQ results, anomalies, create dashboard. Document data quality issues. Prepare Source to Target data mapping documentation for developers Perform DUTSITUATDRregression testing activities. Handle user inquires and production support. Create and maintain project, design, and other required documentation. Conduct trainings and knowledge sharing sessions. Support ISABIT initiatives as required. Additional Responsibilities may include Support the department with data quality architecture, best practices, and patterns. Come up with reusable data quality framework that's parameter driven Work with offshore developers Act as Agile Scrum Master as assigned Assist management with data quality estimation model (to be used for future projects) Consolidate data quality technical specs and maintain in a central location Assist with Controls implementation for Golden SourcesAggregation Layer Qualifications College degree, preferably a B.S. in Computer Science, Engineering, Management Information Systems or a related field or the equivalent Hands-on expertise in developing object oriented programs in a multi-tier data integrationdata management platform in the banking industry. (5 years) Hands-on experience in designing or using relational and dimensional databases in the banking industry. (3 years) Hands-on experience in developing web based applications using .NET (3 years) Hands-on experience in advanced SQL and advanced Excel functions. (3 years) Hands-on experience in using Enterprise Scheduler (Autosys). (2 years) Experienced in waterfall and agile SDLC methodologies. (3 years) Subject-matter expertise in Data QualityData Accuracy (2 years) Knowledge of Informatica Power Center and Informatica Data Quality a plus. Detail-oriented with excellent interpersonal, verbal and written communication, coordination, documentation, analytical, problem solving, leadership, and time management skills. The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities duties and skills required of personnel so classified. We are proud to be an Equal Opportunity Affirmative Action Employer and committed to leveraging the diverse backgrounds, perspectives, and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate in employment decisions on the basis of any protected category. A conviction is not an absolute bar to employment. Factors such as the age of the offense, evidence of rehabilitation, seriousness of violation, and job relatedness are considered in all employment decisions. Additionally, it's the bank's policy to only inquire into a candidate's criminal history after an offer has been made. Federal law prohibits banks from employing individuals who have been convicted of, or received a pretrial diversion for, certain offenses. Department Systems Technology
Associated topics: administrative assistant, asso, associate, document, facilities, operation, operational assistant, operations director, staff, support

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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