Mid-Level Business Intelligence Analyst

Boeing

Mid-Level Business Intelligence Analyst utilizing BI best practices and Generative AI for efficient data solutions at Boeing. Collaborating across teams in Seattle, WA; Berkeley, MO; Hazelwood, MO; or Dallas, TX.

Posted 6/1/2026full-timeSeattle • Montana, Texas, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $105,400 - $152,950 per yearWebsite

Tech Stack

Tools & technologies

Amazon RedshiftAWSBigQueryCloudETLGoogle Cloud PlatformMicroservicesOraclePythonSQLTableau

About the role

Key responsibilities & impact

Design reusable BI information models, views, dashboards, metrics and reports that meet business needs across supply chain and related functions
Translate business requirements into technical designs, user stories and acceptance criteria; validate delivered solutions with stakeholders
Build, optimize and maintain SQL (Redshift/Oracle/Teradata/SQL Server) queries, Extract Transfer Load (ETL)/data wrangling pipelines and data transformations for reliable reporting
Produce analytics deliverables (ad-hoc analysis, trend reports, root-cause investigations) to support decision-making
Prototype and evaluate GenAI/LLM use cases to augment BI workflows (e.g., natural-language querying, automated data summarization, intelligent insights generation, prompt templates for analysts)
Apply prompt engineering best practices: design, test, and optimize prompts and chains for consistent, accurate outputs; document prompt libraries and guardrails
Integrate LLM/GenAI capabilities with BI tools or data platforms where appropriate (e.g., Application Programming Interfaces (APIs), wrappers, microservices) in collaboration with engineers and data scientists
Ensure responsible use of GenAI: implement data privacy, Personally Identifiable Information (PII) handling, output validation, and model risk mitigation practices
Collaborate with data scientists, Machine Learning (ML) engineers, and platform teams on productionizing Artificial Intelligence (AI)-enabled features and understanding model performance and limitations
Develop and deliver stakeholder-facing demos, playbooks, and training materials that show how GenAI augments BI workflows
Work with cloud data platforms (Google Cloud Platform (GCP) and Amazon Web Services (AWS)) to design, develop, and maintain data products — including data ingestion, storage, transformation, and serving layers
Build and validate data products on cloud platforms (BigQuery, Cloud Storage, Dataflow, AWS S3, Redshift, Glue, etc.) and collaborate with platform/engineering teams on deploying them to production
Participate in agile delivery: sprint planning, estimation, development, testing and release activities
Identify opportunities to improve automation, reduce analyst toil, and scale analysis via templated assets and self-service

Requirements

What you’ll need

5+ years of experience in Business Intelligence, Analytics, or Data Engineering roles
Experience with SQL and relational databases (Oracle, Teradata, SQL Server)
Experience working with cloud platforms (GCP and/or AWS)
Experience with core data services (storage, ETL/streaming, warehouses, serverless computing)
Experience building data products on cloud platforms (ingestion, transformation, cataloging, serving)
Experience with BI/visualization tools such as Tableau and/or Power BI and ability to design scalable dashboards and data models
Experience with Python and/or R for data preparation, analysis, and/or prototyping
Experience with data modeling, ETL patterns, data quality practices, and common BI architecture
Experience with Agile, DevOps and release methodologies

Benefits

Comp & perks

health insurance
flexible spending accounts
health savings accounts
retirement savings plans
life and disability insurance programs
paid and unpaid time away from work

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLETLdata wranglingdata transformationsGenAILLMprompt engineeringdata modelingPythonR

Soft Skills

collaborationcommunicationstakeholder engagementproblem-solvingagile delivery