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Reference Data BA

Madison-Davis

Charlotte, NC

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JOB DETAILS
SALARY
$64
SKILLS
Analysis Skills, Artificial Intelligence (AI), Business Analysis, Capital Markets, Communication Skills, Data Analysis, Data Modeling, Data Quality, Data Sets, Documentation, Documentation Models, Enterprise Protection, Financial Services, Information/Data Security (InfoSec), Machine Learning, Metadata, Pricing, Reconciliation, Requirements Management, Risk, Root Cause Analysis, SQL (Structured Query Language), Securities, Training Data Sets, Use Cases, Vendor/Supplier Selection
LOCATION
Charlotte, NC
POSTED
1 day ago
  • Serve as a lead Business Analyst for the build-out of an enterprise Security Master covering multiple asset classes
  • Analyze and document reference data models including securities, instruments, issuers, identifiers, hierarchies, and relationships
  • Work directly with large datasets using SQL to validate data quality, perform reconciliations, and support root-cause analysis
  • Partner with data engineering teams to translate business requirements into logical and physical data designs
  • Define data lineage, ownership, and usage for market data, reference data, and capital markets transaction data
  • Support integration of external data sources such as ratings, indices, pricing feeds, and vendor reference data
  • Collaborate with AI and analytics teams on enrichment, scoring, and entity-linking use cases
  • Drive clarity across ambiguous data problems by aligning stakeholders on definitions, rules, and governance
  • Produce high-quality documentation including business requirements, data mappings, and functional specifications

What You Bring
  • 7+ years of experience as a Business Analyst or Data Analyst within financial services
  • Deep, hands-on expertise with reference data and security master concepts
  • Strong working knowledge of capital markets data, including instruments, trades, positions, and lifecycle events
  • Advanced SQL skills with experience querying large, complex datasets
  • Experience working with market data vendors, identifiers, and symbology (e.G., securities, issuers, hierarchies)
  • Proven ability to partner closely with engineering, data, and product teams
  • Strong analytical mindset with the ability to connect disparate datasets into a coherent model
  • Excellent communication skills with the ability to translate complex data topics to non-technical stakeholders
  • Experience supporting enterprise data platforms or large-scale data modernization initiatives
  • Exposure to data governance, metadata management, or data quality frameworks
  • Familiarity with ratings, indices, or alternative data sources
  • Experience supporting AI or machine learning initiatives from a data definition perspective
  • Background working in front office, risk, or operations data environments



About the Company

M

Madison-Davis

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