Sr Business Intelligence Developer - Onsite

POSITION SUMMARY

Reporting to the Senior Manager of AI & Business Intelligence, the Senior Business Intelligence Developer will play a critical role in establishing and scaling a Business Intelligence Center of Excellence (CoE). This role is responsible for designing, developing, and delivering enterprise BI solutions while defining the standards, data models, and practices that enable scalable, governed analytics across the organization. The individual will be highly hands‑on in the near term (80–90% development), delivering critical dashboards, data models, and reporting solutions.

Over time, the role will evolve toward a broader leadership focus (approximately 70/30), driving standardization, governance, and alignment across BI and analytics teams. The ideal candidate combines strong technical execution with a systems mindset—building solutions that are not only effective in the moment, but reusable, scalable, and aligned to long‑term enterprise data strategy. This position is required to be onsite in Springfield, Missouri.

• Partner with cross‑functional stakeholders to gather requirements and define, standardize, and document enterprise KPIs and business metrics.
• Design and develop scalable, governed BI solutions, including Power BI dashboards, semantic models, and enterprise reporting assets.
• Build BI solutions in a way that establishes reusable patterns, standardized logic, and scalable data models for broader organizational use.
• Own and evolve semantic models and reusable data structures, ensuring consistency across reporting and analytics.
• Collaborate with Data Engineering and Analytics teams to build and optimize robust ETL/ELT pipelines and data models (e.g., Snowflake, dbt).
• Drive improvements in data quality, consistency, and governance across BI workflows.
• Enforce BI development standards, naming conventions, and best practices.
• Optimize BI platform performance, including query efficiency, model design, and cost management.
• Influence and guide partner analytics teams toward standardized, maintainable, and scalable solutions.
• Act as a key liaison between business stakeholders, data engineering, and analytics teams to ensure alignment and scalability.
• Support business users through training, documentation, and enablement of self‑service analytics.
• Identify opportunities to improve efficiency, scalability, and long‑term maintainability of BI assets.
• Operate effectively in ambiguous or evolving data environments, driving incremental improvement and structure.
• All other duties as assigned.

• Minimum Degree
  
  Required:
  
  Bachelor's Degree in Computer Science, Mathematics, Statistics, Economics, or related field (or equivalent experience).
• 4+ years of experience in BI development, analytics, or data engineering roles.
• Strong expertise in SQL and enterprise data modeling (required).
• Advanced proficiency in Power BI and DAX (required).
• Experience building semantic layers, reusable data models, and scalable reporting frameworks.
• Experience with modern data platforms such as Snowflake or Databricks (preferred).
• Experience with dbt or similar transformation tools (preferred).
• Familiarity with CI/CD pipelines and version‑controlled analytics workflows (e.g., Git Lab, Azure Dev Ops).
• Experience working across multiple business domains and stakeholder groups.
• Retail, distribution, or supply chain experience is a plus.

• Strong expertise in data modeling, data warehousing, and BI architecture.
• Proven ability to define and standardize business metrics across teams.
• Deep understanding of data pipelines, data quality, and governance principles.
• Ability to influence without direct authority across decentralized teams.
• Strong analytical and problem‑solving skills.
• Excellent communication skills with the ability to translate between business and technical audiences.
• Ability to balance hands‑on technical execution with strategic thinking.
• Highly organized with the ability to adapt to changing priorities.
• Experience operating in low‑maturity or evolving data environments.
• Continuous learner focused on improving systems, processes, and team capabilities.

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