Senior Business Analyst I

Schneider Electric•Nashville, TN

About The Position

The Business Intelligence Architect serves as a primary analytics partner to Schneider Electric’s Strategic Customers and Segments business. The role works directly with Sales leaders and cross-functional teams to improve business performance through analytics, combining business partnership, solution design, hands-on development, and user adoption. The position owns initiatives from concept through execution and is expected to deliver in the existing environment while helping advance AI-assisted development and modern analytics capabilities. The Business Intelligence organization currently uses SQL, Tableau, and Alteryx and is expanding its toolkit to include Databricks and AI-assisted development tools such as Claude Code. The role develops and maintains analytical solutions, advances scalable capabilities, simplifies processes, improves data accessibility through reusable solutions, and supports reliable, well-governed analytics. The position is based in one of the listed U.S. locations: Nashville, Tennessee; Dallas, Texas; Boston, Massachusetts; or Raleigh, North Carolina. This is a full-time U.S.-based position with an expected annual pay range of USD 101,600–152,400, including base pay and short-term incentives. Schneider Electric describes its total rewards as including medical, dental, vision, and basic life insurance; flexible work arrangements; paid family leaves; well-being programs; 12 holidays and 15 days of paid time off per year; incentives; company share ownership; a 401(k) with match; career-development resources; volunteer leave; and military leave benefits.

Requirements

Strong ownership mentality and ability to independently lead initiatives and drive results.
Demonstrated initiative in leveraging AI and emerging technologies to improve productivity and analytical development.
Strong business partnership and communication skills, including confidence engaging directly with leaders, challenging assumptions, and influencing decisions.
Organized and structured approach to project execution and prioritization amid competing business needs.
Curiosity and adaptability when facing ambiguity, with a commitment to continuous learning and improvement.
Hands-on experience with AI coding agents.
Proficiency in SQL.
Experience with Tableau, Power BI, or similar visualization platforms.
Experience with Alteryx or a similar ETL tool.
Strong critical-thinking and problem-solving skills to address complex business challenges.
Excellent collaboration and active-listening abilities.
Adaptability and comfort navigating change in a fast-paced environment.
Business acumen to connect technical solutions to strategic organizational goals.

Nice To Haves

Familiarity with modern data architecture concepts such as medallion layers and governed data catalogs.
Exposure to conversational analytics such as Genie or equivalent solutions.
Five or more years of experience in business intelligence, analytics, data engineering, or related fields.
Experience independently leading complex analytical initiatives and partnering directly with business stakeholders and leadership teams.
Bachelor’s or master’s degree in Analytics, Engineering, Information Systems, Computer Science, Business, or a related field, or equivalent practical experience.

Responsibilities

Serve as a trusted analytics partner to business leaders and proactively assess performance, translating opportunities or risks into actionable insights and recommendations.
Lead analytical initiatives from stakeholder discovery through solution design and deployment, and own adoption and ongoing improvement with accountability for business outcomes.
Use AI-assisted development tools such as Claude Code to accelerate development and automation and improve troubleshooting and ongoing maintenance.
Design and maintain analytical solutions using SQL, Tableau, Alteryx, and Databricks while supporting a transition toward modern, scalable capabilities.
Identify opportunities to simplify existing processes and eliminate redundant solutions.
Improve data accessibility by developing reusable analytical capabilities.
Drive business adoption through stakeholder engagement and user enablement.
Maintain standards for data quality, validation, documentation, and reliability.
Partner directly with Sales leaders and cross-functional teams to improve business performance through analytical solutions.