Business Intelligence Specialist

Salary range: 95k - 115k + Benefits/Bonus

Client unable to accommodate C2C or Sponsorship

This role serves as the technical backbone for enterprise analytics, responsible for building and maintaining the data models and SQL logic that drive reporting, forecasting, and operational decision‑making. The position focuses heavily on cloud data warehousing, transforming data from financial, operational, and customer platforms into consistent, trusted datasets used across multiple business functions and analytics tools. Instead of primarily producing dashboards, this role establishes the data foundation that powers reporting, planning, and AI‑driven insights across the organization.

Collaborate with teams across Finance, Operations, Development, and Shared Services to convert business problems into scalable analytics solutions.

Manage and enhance analytical data models within a cloud data warehouse, including schemas, transformations, and views that act as system‑wide sources of truth.

Build, optimize, and maintain reusable SQL logic powering analytics models, reporting environments, and AI‑supported applications.

Validate and prepare data generated by Python processes or cloud‑native jobs to ensure downstream readiness.

Work closely with a Data Scientist to coordinate data pipeline outputs, data contracts, and model integration points.

Develop and maintain Power BI semantic models and datasets that rely on warehouse‑layer logic rather than embedding business rules inside reports.

Diagnose and resolve data quality issues across ingestion, transformation, and modeling layers with clear ownership and documentation.

Lead analytics initiatives involving ERP, planning systems, CRM data, and third‑party data sources.

Produce and maintain documentation outlining metrics, analytical logic, data models, and reporting standards.

Support analytics use of AI tools, ensuring proper data governance and alignment with intended analytical outcomes.

Contribute to internal policies on responsible AI usage, including prompt design standards, data access controls, and best practices.

Perform additional duties or projects as assigned.

Bachelor's degree in Information Systems, Analytics, Computer Science, Finance, or related discipline preferred.

Relevant data, analytics, or cloud certifications are advantageous.

3-6 years in business intelligence, analytics engineering, or data analytics.

Strong expertise in SQL and designing reusable analytical logic for production systems.

Hands‑on experience managing analytics models in a cloud data warehouse (Snowflake preferred).

Exposure to data generated through Python pipelines or cloud‑based workloads.

Background in creating analytics frameworks that support multiple business teams.

Experience designing prompts or workflows for enterprise AI tools.

Familiarity with CRM data (ideally Hub Spot), FP&A tools, or financial reporting environments.

Understanding of Azure services used in analytics, such as Data Factory, Container Apps, or storage solutions.

Strong analytical mindset with excellent problem‑solving skills.

Ability to convert technical data concepts into clear business insights.

Strong communication skills‑both written and verbal.

Highly organized, detail‑oriented, and comfortable working in a dynamic environment.

Able to build productive relationships with both technical and non‑technical stakeholders.

All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance.