Title: Technical Business Analyst
Client: Confidential
Location: New Jersey (Hybrid)
Duration: 12 Months
Work Hours: 40 hours/week
Role Objectives
- Analyze data sources data dictionaries business glossary data mappings ETL processes and data within the Data Lakehouse (Databricks) to understand structure relationships dependencies and document data quality rules controls and procedures.
- Ensure new and existing systems are effectively integrated with IT infrastructure and data quality policy.
- Support creation of technical requirements for implementing and maintaining DQ rules in Collibra Data Quality (CDQ) in partnership with Technology and Data Quality Managers.
- Ensure KDEs are governed by DQ rules across accuracy completeness uniqueness timeliness validity and consistency.
- Perform data validations reconciliations QA and UAT; create and maintain test plans execute test cases validate CDQ results and support root cause analysis.
- Collaborate with business users and Collibra developers to support triage in ServiceNow (SNOW) and provide updates in daily scrum calls.
- Support DQ issues management for production issues in SNOW and maintain Data Quality metrics to support reporting solutions.
- Validate DQ metrics scorecards and reports to support coverage and reporting of Data Quality via dashboards.
Qualifications and Skills
- 5 years of experience as a Business Analyst in Data Quality and Data Governance on enterprise platforms.
- Strong hands-on experience with Collibra Data Quality Azure Databricks Unity Catalog Power BI ServiceNow.
- Expertise in Data Quality for regulatory/financial reporting (e.g. FR2052a FRY9C).
- Proficiency in SQL queries ETL processes and scheduling products.
- Skilled in Microsoft Office Suite (Outlook Word Excel PowerPoint Visio).
Preferred Qualifications
- Bachelors degree in Data Management Information Systems or Business Analytics.
- Background in financial services or regulated industries.
- Knowledge of metadata management business glossaries data stewardship KDEs data lineage and data quality concepts.
- Familiarity with other tools in the data ecosystem (data catalogs lineage tools data quality tools).
- Experience developing reports and dashboards in Power BI.