Direct client requirements need for Data Analyst Specialist in McLean, VA

Job Title: Data Analyst Specialist

Location: McLean, VA (onsite)

 

 

Must Have Qualifications:

Candidates must have 1+ years as a true Data Analyst. Must have experience in data analysis, advanced SQL, and Python.  Experience extracting and analyzing data, building and maintaining data models m and working with various data structures and database technologies. Strong communication skills are required and must be able to effectively collaborate with internal stakeholders at all levels. Experience with Snowflake and Databricks is nice to have.

 

Overview

We are seeking a highly analytical and collaborative Data Analyst Specialist to support the Enterprise Business Model (EBM) effort, a strategic initiative focused on modernizing enterprise data through standardized models, improved data quality, and a shared, well-governed data ecosystem.

This role is responsible for driving alignment across the data lifecycle, including data discovery, lineage, profiling, data flow analysis, requirements, and reporting. The specialist will ensure data is accurate, aligned to enterprise models, and ready for consumption across applications and stakeholders.

 

Key Responsibilities

Data Analysis & Pattern Identification

Extract, analyze, and interpret data from enterprise data stores and transactional databases to identify trends, patterns, and anomalies

Validate data consistency and accuracy against defined enterprise data models and business rules

Proactively identify and investigate data discrepancies that may impact downstream consumers

Documenting differences between legacy and future state data

 

Data Profiling & Quality Assessment

Perform detailed data profiling (manual and tool-based) to assess data completeness, validity, and consistency

Leverage data profiling and data quality tools to automate validation where applicable

Document data quality issues, root causes, and recommended remediation actions

 

Cross-Functional Collaboration

Work closely with data teams, application teams, and business stakeholders to understand data flows, transformations, and dependencies

Facilitate working sessions to triage, analyze, and resolve identified data issues

Drive alignment on data definitions, ownership, and quality expectations across teams

 

Data Governance & Model Alignment

Ensure data aligns with enterprise data models, standards, and governance frameworks under EBM

Support data reconciliation efforts across multiple data sources, particularly in transition or dual-data environments

Contribute to documentation of data lineage, transformations, and control points

Support transition of data ownership to producers in alignment with target-state operating model

Maintain metadata, including definitions, lineage, and sensitivity/criticality classifications

 

Communication & Issue Resolution

Communicate findings, risks, and recommendations clearly to both technical and non-technical stakeholders

Track issues, owners, and remediation timelines to ensure resolution

Prepare concise summaries and updates for leadership on data health and risks

 

Historic Data Migration

Support planning and execution of historical data migration, including identification of anomalies and resolution strategies

Validate and test data against target-state models to ensure operational readiness

 

Required Qualifications

 

Technical & Data Skills

• Strong experience working with relational and non-relational databases, including advanced SQL for complex data extraction, transformation, and analysis
• Proficiency in Python for data analysis, validation, automation, and scripting to support data quality and reconciliation processes
• Working knowledge of Excel (advanced functions, pivot tables) and experience handling semi-structured data formats (e.g., JSON, XML)
• Experience integrating with and analyzing data from REST APIs

 

Data Quality, Modeling & Analysis

• Hands-on experience in data profiling and data quality assessments using both manual techniques and data quality tools
• Proven ability to analyze large and complex datasets to identify patterns, anomalies, and inconsistencies
• Experience validating data against enterprise data models, schemas, and business rules, ensuring alignment with target-state architectures

 

Data & Business Alignment

• Strong understanding of data lifecycle management, IT business processes, and alignment of data to business objectives
• Ability to interpret business requirements and support requirements analysis, with focus on upstream (producer) and downstream (consumer) data impacts during transformation initiatives

 

Collaboration & Communication

• Strong facilitation and communication skills, with the ability to lead cross-functional discussions across business, data, and technology stakeholders
• Demonstrated ability to partner with stakeholders to drive alignment and influence data-related outcomes

 

Project & Delivery Execution

• Foundational project management skills, including tracking deliverables, risks, issues, and dependencies across data workstreams
• Self-motivated, proactive, and results-oriented problem solver with strong analytical thinking and communication skills
• Ability to quickly learn new systems and technologies and adapt in a fast-paced environment

 

Preferred Qualifications

• Experience within the mortgage or financial services industry
• Familiarity with Freddie Mac, Fannie Mae, or similar GSE environments
• Experience supporting data modernization, migration or enterprise data programs
• Exposure to data governance, reconciliation frameworks, and control design