Senior Business Intelligence Developer

Senior Business Intelligence Developer

The Opportunity

We need a seasoned BI professional who can own analytics from end-to-end—from data architecture through stakeholder delivery. You'll work across commercial operations data, building solutions that executives actually use to make decisions. This role sits between the data team and business units, so communication matters as much as technical chops.

CORE COMPETENCIES REQUIRED

Technical Pillars:

• SQL (real depth here—query optimization, stored procedures, troubleshooting slow queries)
• Power BI development (DAX, Power Query, interactive reporting)
• Data modeling (you understand fact tables, dimensions, cardinality constraints)
• Python for scripting and automation
• Data warehouse fundamentals

Experience Bar:

• 8+ years building BI solutions or analytics systems
• Proven track record with enterprise-scale data (not hobby projects)
• Hands-on Power BI work (minimum 3 years at this level)
• Ability to gather messy requirements and translate into architecture

SKILL BREAKDOWN

Must-Have (Non-Negotiable ):

• Advanced SQL and relational database knowledge
• Power BI expertise (DAX formulas, data refresh, dashboard optimization)
• Data modeling and dimensional design principles
• Python automation and scripting
• Performance tuning and data quality validation
• 7+ years relevant experience
• Ability to work cross-functionally with business and engineering teams

Nice-to-Have (Differentiators):

• Background in commercial or business operations (finance, supply chain, sales)
• Advanced Python (data science libraries, statistical analysis)
• Cloud platforms (Azure, Snowflake, Databricks)
• ETL tools (SSIS, Talend, or similar)
• Mentoring junior team members

Bonus Points:

• Real-time or streaming analytics experience
• Machine learning application in BI contexts
• Experience with multi-region reporting
• Tableau or Qlik as secondary tools

WHAT YOU'LL ACTUALLY DO

• Design reporting architecture that scales.
• Optimize queries that run slow.
• Push back on unrealistic timelines.
• Partner with business teams who don't always know what they need.
• Build dashboards people actually look at.
• Automate the repetitive stuff with Python.
• Support production issues when something breaks.