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# Senior Business Intelligence Data Analyst

- **Company:** Gainwell Technologies
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $69,400.0 - $99,200.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Information Engineering, Data Infrastructure, IBM Cognos Business Intelligence, Python (Programming Language), Power BI, SQL Databases, Tableau (Software), Scripting, Microsoft Power Automate, Data Analytics, Data Pipelines
- **Published:** July 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f7878809fb1f935e

## About the Role

* 5 years of Data Analytics experience.

 * 5 years of experience coding in SQL. Experience in Python and/or other data scripting languages.

 * Experience utilizing a business intelligence visualization tool (Cognos, Tableau, Power BI, Power Automate etc.).

 * Experience in querying and analyzing and working with data languages and platforms to investigate large and diverse data sets.

 * 4 years of experience working within process management and improvement methodologies - Agile, Lean, Six Sigma, etc.

 * 3 year of experience utilizing and developing within a cloud environment (AWS/Azure preferred).

## Description

The Business Intelligence Business Analyst focuses on building and maintaining scalable data solutions that empower teams with reliable insights. It blends analytics, data engineering, dashboard development, and cross-functional collaboration. The role requires both technical depth and the ability to translate business needs into actionable data products.

Your role in our mission

 * Collaborate with team members and stakeholders to define key business metrics and gather requirements for which insights should be made available at scale.

 * Architect data pipelines, design, and build new dashboards for stakeholders to address their needs.

 * Maintain and improve existing data infrastructure and dashboards based on evolving business requirements.

 * Publish and maintain clear documentation to inform and educate users at scale, gather feedback to identify opportunities for improvement.

 * Identify ways to streamline and improve the efficiency of our data.

 * Implement changes to our infrastructure (optimize SQL queries and data workflows) to improve the landing time of our data.

 * Work with cross-functional teams to identify data needs and gaps and align on solutions.

 * Lead projects end-to-end, see around corners, and provide thought partnership to your team.


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