Data Operations Analyst

Summary

Join Nimble Gravity, a team of outdoor enthusiasts and growth hackers, as a Data Operations Analyst. You'll bridge the gap between business operations and technical data workflows, working hands-on with Python scripts, Databricks notebooks, and LLM API calls to ensure seamless execution of pre-built analytics and AI tools. You'll collaborate with business stakeholders, drive operational efficiency, and translate data insights into actionable strategies. If you enjoy solving business problems with data, working with pre-existing ML models and workflows, and keeping AI processes running smoothly, this role is for you.

Requirements

• 2-5 years of experience in a data-driven role (Business Analyst, Data Analyst, Data Engineer, or similar)
• Proficiency in Python for running and troubleshooting scripts
• Familiarity with Databricks, SQL, and cloud-based data platforms
• Experience in business operations, project management, or program management
• Understanding of AI/ML workflows (even if not building models from scratch)
• Ability to connect technical work with business impact
• Strong problem-solving skills and a proactive approach to operational challenges
• English language proficiency C1/C2 required

Responsibilities

• Execute and monitor Python notebooks and AI/ML workflows in Databricks and other tools
• Work with pre-built AI/ML models and LLM API calls to ensure smooth operation
• Collaborate with business teams to translate data insights into operational actions
• Troubleshoot and optimize data workflows, queries, and automation scripts
• Manage and document data pipelines, processes, and analytics workflows
• Assist with data validation, reporting, and business intelligence tasks
• Coordinate between engineering, analytics, and business teams to ensure data projects align with business goals
• Support AI/data governance, ensuring processes are compliant and scalable

Preferred Qualifications

• Experience with LLM APIs and AI-driven workflows
• Familiarity with workflow automation tools (e.g., Airflow, dbt)
• Experience working with stakeholders across both technical and non-technical teams
• Strong documentation skills for maintaining data workflows