Data Management - Data Analyst - Sr
Spectraforce
McLean, VA, United States
3 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
Data Analysis
Business Logic
Big Data
Data Architecture
Data Discovery
Data Governance
Data Mapping
Database Queries
Data Intelligence
Python (Programming Language)
SQL Databases
Technical Data Management Systems
+6 more
Data Processing
Snowflake
Data Management
Gsuite
Legacy Systems
Databricks
Job description
- Backbook Data Analysis: Lead the data discovery process to identify where legacy data resides today, detailing schemas, tables, and columns required for migration.
- Drive Priority Migrations: Support high-priority and medium-priority migration timelines, including Bankruptcy, Deceased/Estates, Levies & Garnishments, and Charge-Offs.
- Data Mapping & Translation: Map legacy attributes from systems like Profile and CST to destination systems, such as Customer Core and AccountsCBP.
- Discrepancy Resolution: Evaluate and resolve data discrepancies between multiple legacy systems (e.g., Profile vs. CST) to establish the true source of truth for the Bank.
- Define Migration Logic: Collaborate with stakeholders to determine business logic for handling active and ended restrictions across both open and closed accounts.
- Technical Execution: Leverage SQL, Python, Snowflake, and Databricks to write complex queries, perform large-scale data extractions, and validate post-migration data quality.
- Cross-Functional Collaboration: Work closely with Tech Leads, Data Stewards, and Business teams to ensure a standard backbook analysis checklist and framework are established and followed.
Requirements
- Experience: 5+ years of real-world experience working as a Data Analyst, Data Engineer, or in a highly technical data-focused role.
- Core Skills: Extensive hands-on proficiency in Snowflake,Google Suite, Databricks, SQL, and Python
- Data Fluency: Deep understanding of complex data architecture, data quality frameworks, and data manipulation.
- Problem-Solving: Proven ability to dive deep into legacy datasets, understand undocumented schemas, and confidently drive analytical outcomes.
Preferred Qualifications:
- Migration Experience: Prior experience in large-scale data migrations, specifically migrating legacy infrastructure to modern cloud architectures, is a major bonus.
- Domain Knowledge: Familiarity with retail banking data, customer restriction statuses (e.g., Fraud, KYC, Bankruptcy), and case management workflows.
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