Data Operations Analyst

Job Description

Nimble Gravity is seeking a Data Operations Analyst to bridge the gap between business operations and technical data workflows. The ideal candidate will work hands-on with Python scripts, Databricks notebooks, and LLM API calls, ensuring the seamless execution of pre-built analytics and AI tools. This role involves collaborating with business stakeholders, driving operational efficiency, and translating data insights into actionable strategies.

Responsibilities:

• Ensure the execution and reliability of data pipelines, notebooks, and ML workflows within Databricks and similar tools.
• Operate and maintain production-grade AI tools and LLM API calls—ensuring availability, performance, and business continuity.
• Translate complex technical workflows into business impact, partnering with ops, analytics, and leadership teams.
• Identify and resolve data bottlenecks; optimize Python scripts and SQL queries for performance and scalability.
• Maintain clear documentation of processes and data products to support transparency and reusability.
• Validate, monitor, and report on the performance of AI models and analytics outputs.
• Partner with engineering and analytics teams to improve automation and elevate internal tooling.
• Contribute to AI/data governance and compliance frameworks for scalable growth.

Requirements:

• 3–5+ years of experience in data ops, analytics, engineering, or related technical/ops roles.
• Strong hands-on proficiency in Python, with the ability to read, run, and troubleshoot code.
• Experience in production environments working with Databricks, SQL, and cloud-based data platforms.
• Exposure to AI/ML tooling, including working with pre-trained models and external APIs.
• A proactive mindset with a demonstrated ability to connect data solutions to business priorities.
• Strong communication and collaboration skills — you can speak “tech” and “business” fluently.
• English proficiency at the C1 level.

Nimble Gravity offers:

• Opportunity to work with pre-existing ML models and workflows.
• A role focused on solving business problems with data.