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# Senior Legal Business Intelligence Analyst

- **Company:** Morrison & Foerster
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $156,000.0 - $218,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Spreadsheets, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), MicroStrategy, Query Optimization, Power BI, Cloud Services, SQL Databases, Systems Integration, Tableau (Software), Large Language Models, Snowflake, Information Technology, Data Analytics, Star Schema, Data Management, Tools for Reporting, Data Pipelines, Amazon Redshift, Databricks
- **Published:** September 19, 2026
- **Apply:** https://www.seattlejobs.com/job.asp?id=3396610808&tx=VT6762TYD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

1. Bachelor's degree required, preferably in business analytics, data science, computer science, economics, statistics, or a related quantitative discipline.
 2. Four or more years of progressive experience in business intelligence, data analytics, data engineering, or legal operations analytics.
 3. Experience designing and deploying enterprise business intelligence solutions for legal, financial, or other data-intensive functions.
 4. Experience translating open-ended requirements from non-technical stakeholders into defined analytical solutions.

Technical Skills

 1. Advanced proficiency with SQL, including window functions, common table expressions, and query optimization.
 2. Strong experience with enterprise business intelligence platforms such as MicroStrategy, Power BI, Tableau, or QuickSight.
 3. Experience building ETL/ELT pipelines and relational and dimensional data models, including star schema design.
 4. Working proficiency with Python, R, or a comparable language for automation and statistical analysis.
 5. Knowledge of data quality, governance, lineage, business rules, and analytical documentation practices.

Preferred

 1. Advanced degree in business analytics, data science, or a related quantitative discipline.
 2. Experience with legal operations data, including outside counsel spend and matter analytics, in professional services or a similarly regulated environment.
 3. Experience building self-service analytics platforms for large groups of non-technical stakeholders.
 4. Experience developing AI agents, LLM-enabled automation, or prompt-engineered workflows in production.
 5. Experience with cloud data platforms and transformation tooling such as Redshift, Snowflake, Databricks, or dbt.

## Description

Develop, implement, and support business intelligence, data analytics, and reporting solutions for legal matters and strategic client initiatives. Work closely with attorneys, clients, eDiscovery professionals, and other stakeholders to translate complex legal and business requirements into actionable insights and scalable analytical workflows. Serve as a subject matter resource for data analysis, visualization, and data-driven decision-making.

Business Intelligence and Data Analytics

 1. Design, develop, and maintain dashboards, reports, and scorecards for legal, financial, operational, and matter data.
 2. Analyze large and complex datasets and perform ad hoc analysis in response to client, attorney, and leadership requests.
 3. Develop and standardize key performance indicators, metrics, visual templates, and reporting conventions.
 4. Develop self-service analytics capabilities that consolidate data, dashboards, and documentation for stakeholder use.
 5. Replace manual, spreadsheet-based reporting with automated solutions and quantify the resulting impact.

Data Management and Technical Solutions

 1. Develop and optimize data models, queries, integrations, and ETL/ELT processes using SQL and comparable tools.
 2. Work with technology teams and data owners to integrate disparate systems into reliable analytical datasets.
 3. Establish data definitions, business rules, lineage, and quality controls, and resolve data-quality issues proactively.
 4. Follow structured development and change-management practices, including development, test, and production promotion.
 5. Develop solutions in accordance with firm technology, security, confidentiality, and data governance requirements.

Legal and Client Analytics

 1. Partner with attorneys and legal professionals to translate matter and client objectives into analytical requirements.
 2. Develop analytics for matter activity, litigation and discovery metrics, financial performance, and resource utilization.
 3. Analyze outside counsel and vendor spend to surface cost trends, budget variances, and optimization opportunities.
 4. Develop customized reporting for strategic clients and extend successful solutions to additional matters and firm functions.
 5. Prepare executive-ready summaries and KPI scorecards for firm and client senior leadership.

Artificial Intelligence and Innovation

 1. Evaluate and apply emerging analytics, automation, and generative AI capabilities to appropriate use cases.
 2. Develop AI-assisted workflows for classification, pattern identification, anomaly detection, and reporting.
 3. Identify opportunities for responsible use of AI while maintaining appropriate human oversight and validation.

Consulting and Process Improvement

 1. Serve as a technical and analytical consultant to attorneys, clients, eDiscovery professionals, and firm leadership.
 2. Translate open-ended business questions into defined analytical requirements, project plans, and technical solutions.
 3. Develop documentation, standards, and training materials for analytical tools and solutions.


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