Sr Data Analyst

Guild Mortgage Company, closing loans and opening doors since 1960. As a mortgage banking firm, we are dedicated to serving the homeowner/buyer. Our goal is to provide affordable home financing for our customers, utilizing the best terms available while providing a level of professionalism and service unsurpassed in the lending industry.

Position Summary

Guild Mortgage is seeking a Senior Data Analyst with a strong track record of creative thinking and driving transformation in technology-enabled environments and maximizing business process efficiencies. The ideal candidate partners effectively with business and technology leaders to deliver measurable, enterprise-wide transformation initiatives across numerous functional areas. This role requires an Automation & AI-first mindset, leveraging existing and emerging technologies to redesign workflows, improve efficiency, and shape Guild’s future operating model and customer experiences. This role is a key technical position and plays an important role in the organization by performing a number of activities related to the company’s Information Technology functions. The role is primarily responsible, under limited supervision, for executing the data strategy and analysis efforts within the company’s enterprise data platform by eliciting business requirements for data & analytics, identifying Key Performance Indicators (KPIs), documenting functional requirements for various business functions, validating data analysis and collaborating across the enterprise data team to deliver actionable insights to key stakeholders. Responsibilities include working with key stakeholders to assess their data and analytics needs, reviewing and updating logical data dictionary and other supporting documentation, assessing availability and quality of data and researching internal and external data sources.

Compensation 

This role is an exempt position with a Targeted Salary Range of $109,114 to $156,510 annually.

Compensation at Guild is influenced by a wide array of factors including but not limited to local and federal minimum wage requirements, education, level of experience, and applicant’s geographical location.

Essential Functions

• Partner with key stakeholders, including the business unit leaders, Product, Data & Technology teams, to assess their data and analytics needs by eliciting data requirements, and researching internal systems of record and publicly available data sources and assessing their quality of data.
• Requisition and obtain private data sources to support business needs for data and insights.
• Identify translation or transformation requirements for sourced data into the data warehouse.
• Improve quality of sourced data by data curation and validation rules as well as maintaining the Master Data tables.
• Maintain the Logical Data Dictionary (LDD) with data lineage information (field definition, domain, source system, intermediary and destination system(s), translations, transformation rules, display screens, referenced reports, etc.), Data Stewards and Data Custodian info along with versioning for historic analysis and audit trail.
• Ensure consistent delivery of high-quality insights to key stakeholders by reconciling and validating dashboards and reports in a timely manner.
• Document functional / non-functional business requirements for collecting, loading, transforming, curating, processing data and for visualization and distribution of insights.
• Identify internal process improvements for automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Provide actionable insights using analytics tools into customer acquisition, operational efficiency and other key business performance metrics.
• Identify Personally Identifiable Information (PII) data in primary data sources as well as in data architecture, define masking and other data processing rules for special handling of PII data as well as maintain access control lists for visibility of PII data on a need-to-know basis.
• Identify and document the Business Continuity Plan/Disaster Recovery (BCP/DR), and technical requirements for high availability and recoverability for the data architecture.
• Improve the quality of data used for analysis by assessing the accuracy of new data sources and the effectiveness of new data gathering techniques.
• Define Key Performance Indicators (KPIs) and document technical processes to monitor and analyze data warehouse performance and data accuracy.
• Contribute to the team of data professionals by using expertise to answer questions and sharing templates, reusable artifacts with less experienced teammates, enhancing skillsets and competencies of team m