Database Developer / Data Analyst

Meyer Distributing is looking for a Database Administrator to join our Indianapolis, IN team - we are hiring immediately! Meyer Distributing is a leader in automotive specialty products marketing and warehouse distribution.  We are looking for an experienced Database Developer / Data Analyst to build reliable data models, reporting datasets, and BI dashboards. You will partner with operations and leadership to deliver accurate reporting and actionable insights, primarily using SQL Server and Power BI.  

Education/Certification(s):

• Bachelor’s degree in computer science, Information technology or a related field

Requirements for Database Administrator:

• 5+ years of experience in SQL Server development and/or analytics roles with production ownership. 
• Strong T-SQL skills, including complex joins, window functions, and performance-oriented query design. 
• Hands-on Power BI experience (data modeling, DAX basics, dashboard design and publishing). 
• Experience translating business questions into measurable metrics and clear reporting outputs. 
• High attention to detail and a strong data integrity mindset. 

Preferred Qualifications for Database Administrator: 

• Experience working with logistics, distribution, warehouse, ERP, or operations data. 
• Experience building standardized KPI libraries and reusable reporting components. 

Benefits for Database Administrator:

• Medical
• Vision
• Dental
• Disability
• Life Insurance
• 401K with Company Match
• Paid Vacation
• Paid Holidays
• Personal Days Available
• 20% Employee Discount
• Casual Dress Code
• Health Savings Account
• Tuition Reimbursement Options Available

Database Administrator duties include but are not limited to:

• Develop and maintain SQL Server objects (tables, views, stored procedures) that power reporting and analytics. 
• Design and own reporting datasets and semantic layers used by Power BI dashboards. 
• Build Power BI dashboards and reports that support operational and executive decision-making. 
• Define metrics and KPIs with stakeholders; ensure definitions are consistent across teams. 
• Profile and validate data quality; implement checks and reconciliation to build trust in reporting. 
• Optimize reporting queries and models for performance and refresh reliability. 
• Document datasets, KPI definitions, and dashboard usage to enable self-serve analytics.