Business Data Analyst|| Oakland, CA (Hybrid)

Business Data Analyst
Oakland, CA (Hybrid) 
Phone + Skype
Job description:

 

 

Business & Data Analysis

Working closely with business stakeholders to gather, analyze, and document requirements for the data repository project from each finance department to understand data sources, business requirements, and reporting needs.
Partner with Finance, HR, and ITS stakeholders to understand business processes, data definitions, and reporting needs
Translate business requirements into functional and technical specifications for data ingestion, transformation, and consumption
Creating and leading systems requirement documentation standards, including Use Case modeling, User Story creations and narrative description.
Collaborating with the data architect to ensure the planned data repository meets UC Finance business requirements.
Data Lake & System Integration

Serve as a key contributor to the design and evolution of an AWS-based data lake architecture
Work closely with data engineers and architects on integrations using AWS services such as Glue, Lambda, S3, Athena, Lake Formation, and QuickSight
Conducting data profiling and data quality analysis using SQL and Python.
Developing and maintaining mapping documents and source-to-target specifications.
Support API-based, batch, and event-driven integrations across enterprise systems
Delivery & Cross-Functional Collaboration

Act as the primary liaison between business stakeholders, data engineering, analytics, and ITS team
Participating and leading backlog refinement, sprint planning, daily stand-ups, and retrospectives.
Creating test plans, execution of unit testing, and UAT activities for data and integration initiatives.
Ensure solutions align with institutional priorities, data governance standards, privacy requirements, and compliance obligations
Communicating technical information to technical and non-technical personnel at various levels within an organization.
 
Governance, Security & Documentation

Support data governance practices, including data definitions, lineage, access controls, and auditability
Ensure appropriate handling of sensitive financial and payroll/personnel data (PII/PHI where applicable)
Produce clear, thorough documentation including requirements, data models, process flows, and test scenarios
 

 

Strong proficiency in SQL for data querying, analysis, and validation.
Strong knowledge of Python for scripting and data manipulation tasks.
Experience with data warehousing, data lakehouse or data lake concepts, ETL processes, and data modeling.
Solid understanding of AWS data services such as Glue, Lambda, S3, Athena, Lake Formation, and QuickSight
Familiarity with Agile/Scrum methodologies.
Experience with tools such as Atlassian JIRA, Atlassian Confluence and SQL Case Tools such as TOAD or SQL Developer.
Knowledge of extraction, transform and load (ETL) and/or extraction, load and transform (ELT) processes from source to target.
Demonstrated experience performing extensive and comprehensive data repository testing, creating required test plans, and performing unit testing as well as user acceptance testing
Experience with data management, data warehousing, data lake and data lakehouse implementations.
Demonstrated knowledge of business process and analysis functions including reverse engineering, business process and brainstorming maps in Microsoft Visio, and requirements documentation using Atlassian JIRA.
Demonstrated experience with related areas of IT including managed file transfer (MFT) processes, data architecture, data security, web content management, data quality and validation processes, database administration, specifically access management, and data cleanup and conversion.
Firm understanding of data pipelines and processing programs for data integration especially for organizations with multiple locations and source systems.
Excellent analytical and problem-solving skills with attention to detail.
Strong verbal and written communication skills with the ability to translate technical details into business language.
Demonstrated ability to work with others from diverse backgrounds.

 

 

Business Requirement Document on selected use cases
Functional Requirements and User Stories
Acceptance Criteria and Success Measures
Source-to-Target Data Mapping
Business Data Definitions and Glossary
Functional Specifications and Data Integrations
Transformation and Business Rule Definitions (ELT/ETL logic)
Interface and API Requirement Documentation
Security and Access Requirements (in coordination with ITS)
Reporting and Analytics Requirements
Semantic layer and Metric Definitions
Dashboard and Report Specifications (Quick Sight or BI tools)
Data Classification and Sensitivity Documentaton
Privacy and Compliance Requirements (financial and payroll/personnel data)
UAT Test Scenarios and Expected Results
Business Validation and Sign-off Artifacts
Process Flows and Current/Future State Diagrams
End-User and Stakeholder Documentation
Knowledge Transfer and Training Materials
 

 

 

Bachelor’s or master’s degree in computer information system, Data Analytics, Computer Science, Engineering, or a related field.
8+ years of experience as a Business Systems Analyst or a similar role, preferably in data-centric environments.
Solid understanding of AWS data services (Glue, Lambda, S3, QuickSight or similar)
Strong experience with financial systems, including budge and planning, payroll, and personnel data
Proven experience supporting data integration and analytics platforms, preferably in a cloud environment
Preferred Qualifications

Experience in higher education, specifically finance subject area or other complex enterprise environments
Understanding of data governance and concepts such as data architecture, data security, and data quality.
Knowledge of data visualization tools such as Tableau or Power BI