As the Data Analyst reporting to the head of the Enterprise Data Architecture group, you will support the framework required to proactively prevent data issues that would otherwise impact financial, credit, and risk reporting. This framework includes implementing and supporting repeatable data management processes, assessing regulatory and audit observations, and performing analysis on data issues as prioritized through Enterprise Data Governance.
In addition, the Data Analyst is responsible for maturing the data quality practice to the next level and extending the coverage of the practice to new domain areas, such as CCAR.
Candidates must be able to quickly understand the systems, controls, processes, stakeholders, and uses of finance, risk, and credit data domains. Candidates should be attuned to recent regulations and mandates by Federal Reserve related to data quality, metadata and lineage. Using regulatory compliance needs as a driver, the Data Analyst will partner with other functions internally to lead a vision to transform the data quality practice to support enterprise level programs.
•Data Quality Management – Firm wide review of DQ progress, set new policies / efforts, review system & process changes
•Measure and monitor– Baseline assessments of DQ, automate tracking, and scorecard for continuous monitoring
•Support & Investigate – Data profiling, root cause analysis and process improvements
•Drive Change and improvements – Identify and support changes that will prevent DQ issues
•Partner with cross functional business owners, system architects, service owners, and process re-engineers to deliver results in a sprint based model to support the Program roadmap
•Run Cleanups – Identify efforts needed and augment organizational staff to cleanup urgent data issues to make critical data trustable
•Understand Metadata – Know all systems of record, how they’re used, how they’re updated, who stakeholders are, planned changes, data dictionaries, etc.
•Understand the regulations like CCAR, Basel III, BCBS guidelines etc.
To stand out demonstrate:
•Analytical, process, and problem solving skills
•Defining new metrics
•SQL query writing (Oracle preferred)
•User centered designSkills and Requirements:•3+ years leading data quality, metadata, MDM, and other similar initiatives from a technical implementation perspective
•7+ years in data quality or master data management
•5+ years of experience using Data Quality tools such as SAP Information Steward or an equivalent
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