Data Analyst

SpendHQ•Atlanta, GA

1d•Hybrid

About The Position

SpendHQ is a fast-growing Procuretech scale-up and market leader in spend analytics, with more than 100 team members across 10 countries and headquarters in Atlanta and Lyon. Its SaaS solution serves more than 500 global clients and 20,000 users. The Data Analyst plays a client-facing role focused on helping ensure customer success through technical expertise and customer engagement. The position supports and develops scalable data workflows, contributes to analysis and process improvement, and works with senior team members. It collaborates closely with Implementation, Customer Success, and internal analytics teams, as well as Data & Analytics, Delivery, and Solutions.

Requirements

1–3 years of experience in data analytics, including hands-on experience with SQL and data transformation tools.
Proficiency in SQL and Excel.
Strong communication and documentation skills, including the ability to translate technical concepts for business audiences.
Excellent attention to detail and strong data validation and quality assurance capabilities.
Analytical mindset with strong problem-solving and critical-thinking skills.
Ability to identify data anomalies and gaps and develop effective solutions.
Strong organizational skills and ability to manage multiple priorities and projects.
Experience working with clients or stakeholders in a customer-facing environment.
Fluency in written and spoken English, the primary working language.
AI literacy skills.

Responsibilities

Build and maintain strong customer relationships during the refresh process, acting as a trusted data and analytics partner.
Write, test, and implement business rules and data transformations through scalable, repeatable workflows.
Explain technical issues clearly to customers and non-technical stakeholders and help drive issues to resolution.
Support client project delivery through data integration, validation, and quality assurance.
Use modern AI tools to accelerate troubleshooting, streamline repetitive tasks, and improve technical documentation.
Identify opportunities to improve internal processes and increase efficiency, accuracy, and scalability.
Collaborate cross-functionally with Data & Analytics, Delivery, Solutions, and Customer Success to solve challenges and deliver customer outcomes.