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LBA Realty

Data Applications & Analytics Analyst

Full-TimeUpdated on 10/23/2026
No salary listed
Mid
Irvine, CA, USA
In Person
IT OperationsEnterprise Applications

About the job

Requirements
  • Hands-on experience in data analytics, business intelligence, data applications, system integration, or a closely related role.
  • Solid skills working with relational databases, including joins, aggregations, validation queries, troubleshooting, and source-to-target reconciliation.
  • Working experience with a modern business intelligence or dashboarding tool, including report development, basic data modeling, filters, measures, and testing.
  • Exposure to cloud data platforms, data warehouses, lakehouses, or modern data environments.
  • Strong spreadsheet skills, including reconciling data across multiple sources.
  • Ability to translate business requirements into clear data, reporting, or application tasks.
  • Strong attention to detail and willingness to investigate data discrepancies independently.
  • Comfort working between technical teams and non-technical business users.
  • Strong written communication, documentation, organization, and follow-through.
Responsibilities
  • Serve as a primary point of contact for business users with application questions, support needs, or data issues.
  • Respond to day-to-day data and configuration requests across the company’s operational and business systems.
  • Build working knowledge of how data flows through each system, including how it is entered, approved, maintained, and consumed.
  • Partner with business teams to scope, test, and roll out application enhancements, configuration changes, and workflow improvements.
  • Support user access reviews, role assignments, and permission updates across business applications.
  • Triage reporting and application issues by tracing root causes to process, source data, integration, access, or reporting logic.
  • Participate in user testing for system integrations, data migrations, releases, and workflow changes.
  • Document business processes, system workflows, and standard operating procedures.
  • Translate technical issues into clear, plain-language updates for business users.
  • Contribute to data integration work across the company’s cloud data platform, business intelligence tools, and broader system landscape.
  • Help build, test, and monitor pipelines that move source data into centralized reporting environments.
  • Maintain tables, lakehouse structures, warehouse objects, and validation layers that support reporting-ready datasets.
  • Investigate refresh failures, missing records, schema changes, access problems, and data quality exceptions.
  • Coordinate with vendors and consultants to test deliverables and validate technical outputs.
  • Gather requirements from business users and turn them into clear data and reporting needs.
  • Contribute to dashboards, semantic models, validation reports, and operational reporting tools.
  • Build and test measures, calculations, filters, and data models so dashboards are accurate and easy to use.
  • Reconcile report outputs against source systems, Excel files, and business expectations.
  • Improve dashboard usability through better field organization, labeling, visuals, and consistent business logic.
  • Run recurring data quality checks, including reconciliation, duplicate detection, missing values, and source-to-report validation.
  • Document data definitions, transformation logic, system mappings, and reporting assumptions.
  • Flag process gaps that cause inconsistent data and partner with stakeholders to resolve them.
  • Help establish repeatable validation processes, exception reports, and lightweight data quality controls.
  • Keep documentation current so reporting logic can be understood, reviewed, and reused.
  • Support internal AI and automation efforts focused on document analysis, data search, and reporting productivity.
  • Help evaluate and implement AI-enabled tools where they meaningfully improve validation, reporting, or analysis.
  • Document AI-related processes, user guidance, limitations, and governance considerations.
  • Identify opportunities to reduce manual reporting work and make recurring processes more repeatable.
Desired Qualifications
  • Basic scripting experience for data processing, validation, or automation.
  • Experience working with operational and financial systems used in commercial real estate.
  • Background in commercial real estate, asset management, accounting, property operations, or finance.
  • Exposure to APIs, file-based ingestion, data migration, or system integration projects.
  • Familiarity with data governance, access control, row-level security, semantic models, or data quality frameworks.
  • Interest in AI, automation, large language models, and practical business applications.
  • Experience with budget ownership, forecasting, procurement, and vendor management for end-user technology.
  • Background in real estate, financial services, or professional services firms.
  • Prior experience supporting executive users and office-based workplaces.

About the company

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