Remote Data Operations Lead — AI-Driven Processes

Veeva Systems, Inc.; Barcelona; Híbrido; EUR 35.000 - 50.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Diverse international team

Life insurance

Charity bonus

Pension bonus

Fitness reimbursement

Descripción de la vacante

Veeva Systems, Inc. invites a Team Lead for our Data Operations to guide a remote team of 50+ freelancers executing large-scale data generation pipelines.

You will design business processes, drive improvements and remove blockers to boost efficiency and reduce defects. As a first-line manager and servant leader, you will own team KPIs, collaborate with engineering on AI-driven tooling, and ensure daily targets for data quality and volume are met while fostering an autonomous, international

Formación

• Leadership experience coordinating others in a fast-paced environment.
• Strong understanding of process workflows.
• Comfort working remotely in an international environment.
• Ability to distill complex instructions into actionable steps for a large, remote workforce.
• Data-literate, able to identify bottlenecks from performance data.
• Life sciences experience or education is a plus.

Responsabilidades

• Scale leadership of a remote team of ~50, fostering a high-performing environment.
• Identify opportunities to integrate AI into workflows to accelerate web research and data quality.
• Own team KPIs and ensure targets for data quality and volume are met.
• Collaborate with engineering to build AI-driven tooling and automation.
• Drive process architecture to enable cohesive operation.

Descripción del empleo

Veeva Systems, Inc. invites a Team Lead for our Data Operations to guide a remote team of 50+ freelancers executing large-scale data generation pipelines.

You will design business processes, drive improvements and remove blockers to boost efficiency and reduce defects. As a first-line manager and servant leader, you will own team KPIs, collaborate with engineering on AI-driven tooling, and ensure daily targets for data quality and volume are met while fostering an autonomous, international