Top Business Intelligence Jobs in Seattle, WA

Build and maintain finance data models, automated pipelines, dashboards, and reports for planning, forecasting, close, and executive reporting. Govern finance metrics, reconcile data to source systems and the general ledger, resolve data quality issues, and collaborate with FP&A, Accounting, and Data Engineering. Apply BI best practices such as dimensional modeling, documentation, testing, version control, and data governance while translating finance needs into scalable data solutions.

Leads complex fulfillment-center analytics and applied AI initiatives from problem definition through production adoption. Builds scalable data models, pipelines, inspection tools, root-cause analysis, predictive solutions, and self-service analytics. Partners with Product, Engineering, Data Science, and Operations, establishes engineering standards, conducts reviews, mentors junior engineers, and communicates recommendations to senior stakeholders. Requires strong SQL, Python, cloud data, machine learning, visualization, testing, and software engineering expertise.

Analyzes healthcare, claims, customer service, clinical, and operational data to deliver routine and ad hoc reports, dashboards, KPIs, and actionable insights. Designs analytics projects from conception through reporting, develops statistical and data-mining methods, automates reporting processes, and partners cross-functionally with stakeholders to support health plan operations, strategic decisions, and process improvement.

Build internal applications, dashboards, reports, data pipelines, automations, integrations, and data models for procurement teams. Work directly with users to define problems, shape solutions, and improve products based on feedback. Use AI coding agents, product judgment, and technical review to deliver production-ready software. Support deployment, investigate business questions, communicate insights, and help improve AI-assisted development workflows.

Leads business intelligence and analytics engineering initiatives for Snap’s People Team. Designs scalable data pipelines, models, data products, dashboards, and self-service analytics solutions. Translates business needs into technical requirements, conducts statistical analysis, improves data quality and operational reliability, and delivers actionable insights. Owns systems end to end while mentoring team members and communicating effectively with executives, business partners, analysts, and technical teams.

Develops business intelligence solutions using data from diverse sources to deliver insights, visualizations, process automations, and decision support. The role analyzes complex business opportunities, integrates and refines organizational data, presents findings to senior leaders, and recommends technical approaches with minimal direction. Preferred experience includes SQL, Python, Databricks, Power BI, Power Apps, Power Automate, predictive modeling, and healthcare analytics.

Build and maintain data pipelines, SQL queries, data models, database structures, and centralized data warehouse capabilities. Clean and validate data, develop reporting datasets and solutions, support KPI tracking and historical analysis, and collaborate with Finance and Revenue Operations. Investigate data gaps, troubleshoot integrations, and independently deliver reliable technical solutions.

Develops, validates, documents, deploys, and maintains Amazon QuickSight dashboards in a secure CMS environment. Translates stakeholder requirements into interactive visualizations, performs SQL-based ETL and data-quality validation, supports Tableau analytics, manages UAT and dashboard lifecycles, troubleshoots technical issues, and documents data workflows. The role collaborates with analysts, data scientists, CMS stakeholders, QIO staff, and other teams while supporting healthcare and regulated data initiatives.

Owns Power BI reporting and analytics for Digital, including internal dashboards, campaign pacing, client-facing intelligence products, contact data health, and data delivery monitoring. Builds DAX reporting logic, automated alerts, budget tracking, segmentation, benchmarking, and trend analysis. Partners with IT, Data Engineering, CRM, and audience teams while transitioning an externally developed platform in-house. Serves as the senior reporting subject matter expert for stakeholder and client-facing analytics.

Supports the development and maintenance of Qlik dashboards, reports, and data visualizations. Performs data analysis, validates reporting outputs, identifies trends and anomalies, translates business requirements into reporting solutions, troubleshoots data issues, and helps maintain metrics and KPIs. Collaborates with business stakeholders and develops knowledge of organizational data sources, business intelligence practices, and data governance standards.

Own executive, board, investor, financial, and operational reporting for leadership. Build scalable dashboards, define consistent KPIs, reconcile data across systems, investigate performance changes, and translate complex business questions into actionable insights. Partner with Strategy, Finance, and senior leaders to automate recurring reporting, improve data accuracy, and support actuals-versus-budget-versus-forecast analysis.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Develop dashboards, reporting, and analytics solutions for business teams; monitor performance trends, data quality, risks, and key metrics; investigate complex questions; support A/B testing and instrumentation; and communicate actionable insights to technical and non-technical stakeholders. The role also requires expertise in profit drivers, unit economics, campaign and funnel performance, and the company’s analytics infrastructure.

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

The Business Intelligence Analyst queries cloud data, builds dashboards and recurring reports, validates data integrity, and delivers actionable insights to business leaders. The role embeds AI tools into reporting, documents data definitions and processes, automates manual work, and partners with FP&A, Business Operations, and Data Engineering. It requires SQL, Excel, BI reporting experience, and practical AI application, with Python, R, Git, and dbt listed as preferred skills.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

The Business Intelligence Engineer analyzes complex internal and external data to solve business problems and deliver actionable insights to decision-makers. Responsibilities include integrating, analyzing, summarizing, and presenting data; conducting root cause analysis; using SQL, SAS, Databricks, and advanced Excel; and supporting data-driven business decisions. This is a remote role with occasional travel for training or meetings.

Own production Power BI development, including reports, dashboards, semantic models, advanced DAX, Power Query, SQL, and dimensional modeling. Design, deploy, troubleshoot, and support scalable analytics solutions; modernize legacy BI systems; improve data quality, security, performance, and release practices; and collaborate with Product, Analytics, Engineering, and business stakeholders. Preferred experience includes Microsoft Fabric, source control, CI/CD, semantic model tools, and regulated industries.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

Supports the Product Innovation Team by modifying and optimizing SQL queries, visualizing data with BI tools, identifying insights, and analyzing enhancements. Participates in coding, testing, documentation, and discussions while providing customer service and managing multiple tasks. The internship requires at least 30 hours per week and emphasizes advanced Excel and visualization skills, plus familiarity with Python and SQL.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.

Develop and support enterprise BI solutions, including dashboards, reports, governed datasets, data marts, and ETL/ELT processes. Translate business requirements into technical designs, perform data analysis and validation, troubleshoot production issues, and maintain documentation, governance, security, and data-quality standards. Lead-level candidates will guide technical decisions, mentor team members, and coordinate complex initiatives and incidents.

Develop and maintain Power BI reports, dashboards, apps, and reusable semantic models using SQL, DAX, and Power Query. Own day-to-day Power BI platform operations, including workspaces, publishing, licensing, refreshes, gateways, permissions, and content lifecycle. Translate stakeholder requirements into decision-ready reporting experiences, validate data and calculations, support testing and releases, troubleshoot issues, and coordinate with engineering and security teams. Coach report authors and promote governed, reliable self-service analytics.

Lead CX data intelligence initiatives using SQL, dashboards, analytical models, and AI/LLM techniques. Analyze customer journeys, operational metrics, churn risks, and retention indicators; develop insight agents and self-service reporting; define CX health metrics; and translate findings into strategic recommendations, process improvements, and experiments. Partner with operations, support, product, data, and engineering teams while maintaining data quality, governance, and documentation.