Data & AI Analyst

About the role

The Data & AI Analyst (Operations) will be a core member of the Business Operations team, sitting at the intersection of customer implementation, internal tooling, and data operations. This is a hands-on, technical role that blends data work with product-like ownership of the internal tools and workflows that power Moab's operations.

What You'll Do

• Maintain, improve, and build new internal tools (including AI-powered tooling) used across operations and customer enablement.
• Own customer data migrations end-to-end: map, transform, validate, and load data into Moab's schema using our Python SDK and API, supporting everything from mid-market implementations to bespoke enterprise engagements.
• Design and maintain a library of Python scripts and reusable transformation utilities that make customer onboarding repeatable and scalable.
• Define and enforce standards for data migrations (canonical schemas, QA practices, and documentation).
• Build and maintain reporting and BI solutions (Power BI, SQL-based dashboards) for internal stakeholders and customers, covering implementation progress, data health, and operational metrics.
• Partner with Engineering and Business Operations to resolve data quality issues, enhance the SDK, and improve internal workflows.
• Contribute to process documentation, internal libraries, and cross-functional enablement resources.

What You Need

• 0–5+ years of experience in a data analyst, implementation analyst, or technical operations role.
• Strong proficiency in Python and SQL; experience working with APIs and SDKs.
• You don't just write scripts, you think about how to make them better over time.
• Understanding of data modeling, data transformation, and ETL concepts.
• Experience with Power BI (or similar BI tools), or the ability to learn quickly.
• Comfort working in Git/GitHub and collaborating on code in a team environment.
• Excellent communication skills and a high attention to detail.
• A proactive, ownership-driven mindset; able to balance speed and precision in a fast-paced environment.

Nice to Haves

• Experience with customer data migrations or data integrations in a SaaS environment.
• Familiarity with AI/LLM-based tooling or workflow automation.
• Ability to own ETL / data pipelines using existing vendors (e.g., Fivetran).
• Interest in building standardization and automation for scaling data processes.