Solutions Data Analyst

About SpendHQ

SpendHQ is a fast-growing and dynamic Procure tech Scale-up with an incredible collaborative company culture. Our team is constantly innovating – we invented performance management for procurement and we are a market leader and innovator in spend analytics. We provide procurement teams with the tools they need to drive value for their organization, and we have fun doing it.

The SpendHQ SaaS solution has been on the market for over 10 years. Our clients are recognized market leaders from both mid-size organizations and large, multinational corporations. There are 20,000+ SpendHQ users across 500+ global clients.

It is thanks to each of our employees that we are where we are today. We proudly have over 100 team members in 10 countries with headquarters in both Atlanta and Lyon. But we are not stopping here. SpendHQ is taking on new challenges and we look forward to continuing to grow the company and team.

The Solutions team bridges the gap between the Sales, Delivery, Product and Customer Success. The team exists to accelerate and enhance the sales process by adding credibility, objectivity, and subject matter expertise during the prospect’s evaluation of our platform. SpendHQ’s Solutions Consultants work closely with our sales team to provide support for large deals, analyzing the needs of our prospects to demonstrate how SpendHQ can address their pain points and collaboratively determine the best solution.

The Solutions Data Analyst supports this mission by preparing, analyzing, and validating data used throughout the solution evaluation process. Working primarily with internal teams, you will transform complex procurement datasets into accurate, meaningful insights that help SpendHQ demonstrate platform capabilities and design appropriate solutions.

This is an analytically focused, non-client-facing role. It is ideal for someone who enjoys working with data, solving complex problems, learning new technologies, and collaborating behind the scenes to support successful sales and solution outcomes.

• Support data collection and data transformation of spend data used for POC or Data Health Check.
• Analyze and map complex datasets to identify trends, anomalies, categorization opportunities, and actionable insights.
• Ensure high confidence categorization leveraging SpendHQ categorization tools and processes
• Assess data quality, completeness, consistency, and suitability for use within the SpendHQ platform.
• Perform data reconciliation and quality-control checks to ensure analytical accuracy.
• Document data assumptions, transformation logic, limitations, and findings.
• Create repeatable analytical workflows that improve efficiency and consistency.

• Support Solutions Consultants with the data and analysis required for sales opportunities (POCs and Data Health Check)
• Translate business and procurement requirements into clear analytical and technical specifications.
• Assist with technical discovery analysis and POC scoping
• Prepare internal summaries of data findings, potential risks, and considerations.
• Help confirm feasibility of data-related success criteria for POCs.

• Investigate data-processing issues and work with data teams to identify root causes.
• Test platform functionality using processed spend data.
• Support the validation of AI/ML-driven classification, enrichment, and insight-generation capabilities.
• Evaluate analytical outputs to ensure they are accurate, consistent, and aligned with the prospect business requirements.

• Identify opportunities to automate repetitive data preparation and validation activities.
• Collaborate with Product and Engineering to investigate technical issues and provide structured feedback.
• Develop standardized processes, templates, and quality-control procedures.
• Track internal metrics related to data readiness, analytical quality, and solution-support efficiency.

• Bachelor’s degree in Data Analytics, Data Science, Information Systems, Engineering, Business, Economics, Supply Chain, or a related field.
• At least one year of experience in data analysis, business intelligence, SaaS, procurement analytics, consulting, or a related field.
• Experience cleaning, transforming, validating, and interpreting structured data.
• First experience with Excel, SQL, Python, business intelligence tools, or data-analytics tools is…