Sr Data Analyst

Guild Mortgage•,

6d•$109,114 - $156,510•Onsite

About The Position

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.

Requirements

Bachelor's Degree in Computer Science, Data Science or related quantitative field is required.
Minimum 5 years' experience in Data Analyst related role(s) and two of those years spent in a senior technical level role(s) required.
Highly proficient with eliciting business requirements, documenting user stories, analyzing data sources, and assessing data quality.
Highly proficient in data analysis, technical documentation, logical data dictionary, data validation rules, acceptance criteria, software development lifecycle (SDLC) such as Scrum and IT Service Management (ITSM) – ITILv4.
Experience in identifying data integrations needs using Extract, Transform and Load (ETL) tools and modern data pipes.
Proven experience with querying and analyzing data from SQL relational databases such as AuroraDB, IBM DB2, MemSQL, MS SQL Server, MySQL, Postgres, Snowflake, and NoSQL Databases such as Cassandra, DynamoDB, Redis, MongoDB.
Experience collecting structured, semi-structured and unstructured data in various popular formats and sourced from internal core systems as well as 3rd partner providers such as Google Analytics, Facebook Insights, Zillow, CoreLogic, MLS Data, Public Records, and Property Data.
Experience using collaboration tools such as Microsoft Office or Google G-Suite as well as Jira, Confluence, and Microsoft SharePoint.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytical skills to document processes supporting data transformation, data structures, metadata, dependency and workload management.
Strong data governance skills to ensure highest quality of data is made available for data analysis and accuracy in reporting.
Problem solver with an ability to work as a team towards a solution.
Ability to prioritize multiple tasks in a deadline-driven environment, strong sense of urgency and responsiveness.
Strong detail orientation and highly organized with proven ability to lead effectively and drive results in a matrixed management environment.
Ability to think critically, including the ability to evaluate facts and data to draw conclusions, determine the downstream impact of decisions and associated risks.
Excellent verbal and written communication skills plus demonstrate strong leadership capabilities.
Strong interpersonal and team building skills.
Self-starter with the demonstrated ability to learn/adapt to new technologies and techniques.
Excellent verbal and written communication skills required.
Highly organized and detail-oriented; ability to work in a fast-paced, metrics-driven environment required.
Proficiency in Microsoft Office Suite, Word, Excel, Wiki, collaborative cloud-based programs, and third-party software applications required.
Commitment to company values.
Customer Service - Proactive attention to each person.
Integrity - Do and say what's right.
Respect - Treat others with dignity.
Collaboration - Listen and work together.
Learning - Seek knowledge and strive for improvement.
Excellence – Deliver the unexpected.
Work is primarily sedentary; mobility in an office setting.
Frequent use of computer keyboard and mouse.
Ability to accurately interpret sounds and associated meanings at a volume consistent with interpersonal conversation.
Regularly required to accurately perceive, distinguish and interpret information received visually and through audio; e.g., words, numbers and other data broadcasted aloud/viewed on a screen, as well as print and other media.
Office environment – moderate noise, no substantial exposure to adverse environmental conditions.
Learn new tasks, remember processes, maintain focus, complete tasks independently, and make timely decisions in the context of a workflow.
This role requires effective adaptation to workplace stressors, including customer service complaints, security responsibilities, and competing priorities.
Must be able to adhere to process protocol. Must be able to apply established protocols in a timely manner.
Work is primarily performed during the business week, Monday - Friday.

Nice To Haves

Master’s Degree in business administration (MBA) or related to the position or equivalent, preferred.

Responsibilities

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 members, and sharing business domain knowledge throughout the team.
Participate in stakeholder reviews and design sessions.
Provide data, reports, and information to management as needed.
Identify, track, and monitor trends and avoidable technology-related errors; work across functions to develop complex solutions, improvements, and stop-gaps.
Focus on the continual improvement of policies, procedures, and processes falling under scope of authority.
Use expertise to resolve high level issues that cannot be solved by teammates.
Stay abreast of latest technology trends and participate in high-level decisions impacting the direction of Information Technology function.
Consistently monitor and model platform usage, database sizes, compute resources and third- party costs to ensure that the data team’s spend is as cost-efficient as possible.
Champion data transformation to new ways of working and generating insights.
Drive strong communications, partnerships, and stakeholder management with senior leaders, functional managers and staff.
Perform other duties as assigned.