This position may be offered to a candidate authorized to work in the US for his/her/their stated employer, without any restrictions which would prevent the candidate from working on the proposed assignment for the duration of the assignment period.
Candidates must have 7+ 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 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. Schedule: Standard Shortlisting Deadline: July 1st Interview Information: Rounds: 2 rounds Duration: 30 mins Interview Type: MS Teams - Video Mandatory Interview Placeholders: 7/6, 10:00 10:30 am | 7/6, 2:00 2:30 pm | 7/7, 10:00 10:30 am | 3:00 3:30 pm Interview Debrief: TBD will be scheduled will all suppliers once interviews are completed. Job Title: Data Analyst Specialist 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 o Extract, analyze, and interpret data from enterprise data stores and transactional databases to identify trends, patterns, and anomalies o Validate data consistency and accuracy against defined enterprise data models and business rules o Proactively identify and investigate data discrepancies that may impact downstream consumers o Documenting differences between legacy and future state data Data Profiling & Quality Assessment o Perform detailed data profiling (manual and tool-based) to assess data completeness, validity, and consistency o Leverage data profiling and data quality tools to automate validation where applicable o Document data quality issues, root causes, and recommended remediation actions Cross-Functional Collaboration o Work closely with data teams, application teams, and business stakeholders to understand data flows, transformations, and dependencies o Facilitate working sessions to triage, analyze, and resolve identified data issues o Drive alignment on data definitions, ownership, and quality expectations across teams Data Governance & Model Alignment o Ensure data aligns with enterprise data models, standards, and governance frameworks under EBM o Support data reconciliation efforts across multiple data sources, particularly in transition or dual-data environments o Contribute to documentation of data lineage, transformations, and control points o Support transition of data ownership to producers in alignment with target-state operating model o Maintain metadata, including definitions, lineage, and sensitivity/criticality classifications Communication & Issue Resolution o Communicate findings, risks, and recommendations clearly to both technical and non technical stakeholders o Track issues, owners, and remediation timelines to ensure resolution o Prepare concise summaries and updates for leadership on data health and risks Historic Data Migration o Support planning and execution of historical data migration, including identification of anomalies and resolution strategies o Validate and test data against target-state models to ensure operational readiness Required Qualifications Technical & Data Skills o Strong experience working with relational and non-relational databases, including advanced SQL for complex data extraction, transformation, and analysis o Proficiency in Python for data analysis, validation, automation, and scripting to support data quality and reconciliation processes o Working knowledge of Excel (advanced functions, pivot tables) and experience handling semi-structured data formats (e.g., JSON, XML) o Experience integrating with and analyzing data from REST APIs Data Quality, Modeling & Analysis o Hands-on experience in data profiling and data quality assessments using both manual techniques and data quality tools o Proven ability to analyze large and complex datasets to identify patterns, anomalies, and inconsistencies o Experience validating data against enterprise data models, schemas, and business rules, ensuring alignment with target-state architectures Data & Business Alignment o Strong understanding of data lifecycle management, IT business processes, and alignment of data to business objectives o Ability to interpret business requirements and support requirements analysis, with focus on upstream (producer) and downstream (consumer) data impacts during transformation initiatives Collaboration & Communication o Strong facilitation and communication skills, with the ability to lead cross-functional discussions across business, data, and technology stakeholders o Demonstrated ability to partner with stakeholders to drive alignment and influence data-related outcomes Project & Delivery Execution o Foundational project management skills, including tracking deliverables, risks, issues, and dependencies across data workstreams o Self-motivated, proactive, and results-oriented problem solver with strong analytical thinking and communication skills o 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
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Background Check : No
Drug Screen : No