Data Product Operations Lead

About the role

Own end-to-end success of a data pipeline, from early experiments to scaling up production systems that generate high-quality audio data at high volumes.

Design and run pipelines that process a high volume of audio data with reliability, quality, and efficiency.

Work with researchers at leading AI labs to identify new model capabilities and turn them into concrete data workflows and project plans.

Lead cross-functional workstreams across Ops, Product, and Engineering to build scalable “data factory” systems.

Monitor and improve pipeline health, spotting and fixing issues in sourcing, quality, or process.

Drive impact with metrics, using throughput, quality, and cost to prioritize and improve.

Take full-stack accountability across operations, product, engineering, and customers, solving bottlenecks and ensuring delivery.

Responsibilities

• Own end-to-end success of a data pipeline, from early experiments to scaling up production systems that generate high-quality audio data at high volumes.
• Design and run pipelines that process a high volume of audio data with reliability, quality, and efficiency.
• Work with researchers at leading AI labs to identify new model capabilities and turn them into concrete data workflows and project plans.
• Lead cross-functional workstreams across Ops, Product, and Engineering to build scalable “data factory” systems.
• Maintain pipeline health, spotting and fixing issues in sourcing, quality, or process.
• Drive impact with metrics, using throughput, quality, and cost to prioritize and improve.
• Take full-stack accountability across operations, product, engineering, and customers, solving bottlenecks and ensuring delivery.

Requirements

• 2–6 years in high-intensity environments (e.g. founder, strategy consulting, or venture-backed ops).
• Technical foundation in CS, Industrial Engineering, or similar; SQL required.
• Systems thinker who can spot leverage points and design for scale and durability.
• Strong product intuition, able to work with engineers and researchers to get to the right answer fast.
• A high-execution operator: fast, detail-oriented, and uncompromising on quality.
• Collaborative and low-ego, willing to roll up your sleeves.
• A track record of extreme ownership, caring about outcomes over tasks.
• Experience in data, ML, or large-scale operations.

Qualifications

• Technical foundation in CS, Industrial Engineering, or similar; SQL required.
• Experience in data, ML, or large-scale operations.

Skills

• Technical foundation in CS, Industrial Engineering, or similar; SQL required.
• Experience in data, ML, or large-scale operations.

Benefits

• Competitive salary and equity package.
• Flexible PTO policy.
• Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans.
• Paid lunch and dinner in the office, every day through DoorDash.
• 401k access.

Pay

$120K - $200K

Schedule

Full-time