Job Title: Data Analyst (Mortgage Domain)
Location: McLean, VA (5 Days Onsite) - F2F Interview
Required Skills: - Python/ SAS, SQL & Mortgage Domain
Job Summary
We are seeking a Data Analyst with strong SQL expertise and experience in the Mortgage industry to support data analysis, reporting, and business decision-making. The ideal candidate will have hands-on experience working with mortgage servicing, loan origination, underwriting, or secondary mortgage data, along with the ability to analyze large datasets, identify trends, and collaborate with business and technology teams.
Responsibilities
Analyze and interpret large mortgage datasets to identify trends, anomalies, and business insights.
Develop complex SQL queries, stored procedures, and data validation scripts.
Gather and analyze business requirements from stakeholders.
Create dashboards, reports, and KPIs using reporting and visualization tools.
Perform data profiling, cleansing, reconciliation, and quality assurance.
Support UAT by validating data accuracy and business requirements.
Collaborate with business users, developers, QA, and product teams throughout the SDLC.
Investigate production issues, perform root cause analysis, and recommend solutions.
Document business rules, data mappings, source-to-target mappings, and functional specifications.
Ensure compliance with data governance and regulatory requirements.
Required Qualifications
Bachelor's degree in Computer Science, Information Systems, Finance, or a related field.
Experience in the Mortgage industry (Loan Origination, Servicing, Underwriting, Secondary Mortgage, Capital Markets, or Default Management).
Experience with relational databases such as Oracle, SQL Server, PostgreSQL, or Snowflake.
Strong analytical, problem-solving, and data validation skills.
Experience with Agile/Scrum methodologies.
Excellent communication and stakeholder management skills.
Preferred Qualifications
Experience with Power BI, Tableau, or similar BI tools.
Knowledge of Python or Excel for data analysis.
Experience with ETL processes and data warehousing.
Familiarity with cloud platforms such as AWS or Azure.
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