Sr. Data Operations - AI Products

As a Sr. Data Operations, you will play a critical role in launching and scaling AI products, optimizing data workflows, and driving strategic enablement across the organization. You will work at the intersection of data, product, and business—leading initiatives to enhance how data is captured, processed, and utilized to accelerate decision-making. Your responsibilities will include shaping and evolving our data operations framework, enhancing feedback loops, and embedding scalable and efficient processes that foster experimentation, innovation, and long-term growth.

Key Responsibilities:

• Drive the operational scaling of data products to ensure their robustness, performance, and readiness for wider adoption across business units.
• Lead the implementation and continuous improvement of data operations processes for efficiency, scalability, and accuracy.
• Develop, maintain, and scale internal tools supporting data workflows, AI enablement, and collaboration across teams.
• Execute strategic data initiatives aligned with business goals, delivering measurable impact.
• Design and evolve core data processes to support operational excellence, model performance, and product experimentation.
• Optimize the use of tools for data ingestion, transformation, storage, and observability to enable seamless data accessibility and reliability.
• Identify and resolve complex data workflow issues to ensure high system reliability and responsiveness.
• Contribute to long-term data strategy planning by providing operational insights and identifying opportunities.

Qualifications:

• Minimum of 5 years of experience in operations, business operations, consulting, product, product operations, or data analysis.
• Experience leading cross-functional projects and teams, managing multiple projects simultaneously.
• Strong team player with the ability to connect people and teams to the company vision.
• Proactive mentality and desire to make a significant impact.
• Strong English skills, both written and verbal.
• Strong SQL skills and good understanding of data science definitions and terms.