Senior Engineer, Business Intelligence

Enterprises•Bentonville, AR

About The Position

Walton Enterprises is seeking a skilled, highly motivated, and entrepreneurial Senior Engineer, Business Intelligence to transform complex enterprise data into actionable insights through advanced SQL, data modeling, and business intelligence solutions. The role builds and maintains the analytics and visualization layer used by Walton Enterprises teams to support data-informed decisions. It turns raw enterprise data into governed metrics, curated data models, production dashboards, and reusable self-service reporting tools. The position partners with business stakeholders, software engineering, and infrastructure teams to ensure analytics are accurate, secure, actionable, and aligned with business needs. It supports informed decision-making by helping stakeholders define business questions, creating reporting solutions and consistent data definitions, and enabling self-service analytics across the organization. The role is part of the Data Strategy and Insights team.

Requirements

Bachelor’s degree in analytics, statistics, computer science, information systems, business, or a related field, or equivalent professional experience.
Five to seven years of experience in data analysis, business intelligence, analytics engineering, or a related field.
Demonstrated proficiency in SQL, including performance tuning of complex queries against large datasets.
Hands-on experience with data warehouses.
Hands-on experience with Google BigQuery or a comparable cloud-based data warehouse.
Proven experience building and maintaining production dashboards using Looker, Looker Studio, Power BI, or comparable visualization tools.
Demonstrated examples of data visualizations or analyses that influenced how a team operated or what a stakeholder decided.
Experience defining and governing shared metrics across multiple stakeholder groups.
Advanced SQL, data visualization and dashboard design, data storytelling, data modeling, and semantic-layer design for self-service analytics.
Business acumen and the ability to translate ambiguous business questions into structured, analyzable problems.
Strong communication and collaboration skills with technical and nontechnical audiences.
Data-quality, documentation, and data-stewardship discipline.
Demonstrates discretion, integrity, and expertise while serving as a trusted advisor to principals and colleagues.
Collaborates respectfully and effectively with others, contributing to a supportive, team-oriented environment.
Approaches challenges with curiosity, bold thinking, and a commitment to continuous learning and innovation.
Maintains a strong focus on results while consistently exercising sound judgment and decision-making.
Brings a visionary mindset, planning strategically for the future with imagination and insight.
Demonstrates a commitment to excellence and actively engages with others to accomplish shared goals.
Successful completion, where permitted by state law, of a confidentiality agreement and background check; must provide proper identification verifying eligibility to work in the United States on the first day of work.

Nice To Haves

Experience with programming languages such as Python or advanced statistical-analysis software.
Experience working with accounting, investment, philanthropic, or family-office data.

Responsibilities

Write, optimize, and maintain advanced SQL queries against the enterprise data warehouse to source, join, and validate data for analysis.
Design and maintain curated data models, views, and a governed semantic layer for reusable enterprise data and self-service reporting.
Build and maintain production dashboards and data visualizations, from requirements gathering through implementation and user adoption.
Establish and document shared metric definitions, data dictionaries, and reporting standards to promote consistency across teams.
Partner with stakeholders to frame business questions and translate analysis into clear recommendations and actions.
Develop data-quality checks and monitoring within reporting solutions, investigate discrepancies, and work with business and engineering partners to resolve root causes.
Use AI-assisted tools to accelerate analysis and documentation, validating AI-generated output before sharing it with stakeholders.
Train and support business users in self-service reporting to increase adoption and reduce recurring ad hoc reporting requests.
Collaborate with software engineering and infrastructure teams regarding data availability, access controls, and upstream data-pipeline requirements.
Perform other duties as needed to support the Data Strategy and Insights team.