Data Product Manager, AI Data Platform

About the Team

The Data Solutions Team supports the company’s data-driven business model by ensuring a steady supply of large-scale, high-quality labeled data as the business expands. The team works with both structured and unstructured data to surface insights and turn them into practical products that support rapid growth. Its scope includes building infrastructure, managing recognition capabilities, and coordinating global labeling delivery.

About the Role

This position is for a Data Product Manager who will take ownership of, and continuously improve, the data infrastructure layer that powers an AI data annotation platform. The role sits at the intersection of product management and data engineering. You will shape the product direction for data pipelines, data quality systems, access control governance, and scalable delivery mechanisms, while still being close enough to the technical layer to understand schema design, pipeline orchestration, and quality validation. The goal is to convert complex data needs into dependable, standardized, and secure data products that support downstream labeling work at scale.

Key Responsibilities

• Set the product direction and roadmap for data infrastructure, covering ingestion, transformation, data quality assurance, delivery pipelines, and metric governance.
• Create and maintain standards for data assets, including a shared metric dictionary, pipeline coding patterns, and quality service-level agreements.
• Plan and implement role-based access controls across data assets to support security and policy compliance across teams.
• Convert business labeling needs into clear pipeline requirements and collaborate with data engineers to design, build, and maintain ETL/ELT processes.
• Identify and prioritize product enhancements based on business outcomes, efficiency goals, and future scale requirements.
• Perform data modeling, define schemas, and ensure consistent handling of ingestion sources such as CSV, SQL-Hive, JSON, and API feeds.
• Track pipeline reliability, throughput, and SLA performance, then lead issue analysis and improvement efforts.
• Work closely with Engineering, Operations, QA, and Platform Product Management teams to make sure data is ready for feature modules.

Qualifications

The ideal candidate should hold a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a similar technical discipline. A minimum of 3 years in data engineering or data platform work is required, including at least 1 year in a product management or product ownership role. Strong SQL ability is essential, particularly with Hive or Spark SQL, along with working Python knowledge for data processing and automation. Experience with Airflow, Spark, Flink, and ETL/ELT design is expected, as well as practical exposure to data governance practices such as RBAC, quality monitoring, SLA management, and lineage tracking. A solid grasp of data warehousing, dimensional modeling, and large-scale data architecture is also important. Candidates should be able to write clear PRDs, think analytically, and influence cross-functional stakeholders effectively.

Preferred Experience

• Experience designing metric or KPI frameworks and using BI tools such as Grafana, Tableau, or internal dashboards.
• Familiarity with data security and compliance practices, including data classification and access auditing.
• Background in building or operating large-scale annotation or labeling data platforms.
• Understanding of ML data pipelines, including training data management, golden dataset curation, and data sampling approaches.
• Exposure to agile delivery methods.
• Experience in consumer-facing or enterprise SaaS products.

About the Company

The company is a leading destination for short-form mobile video, with a mission to inspire creativity and bring joy. Its global headquarters are located in Los Angeles and Singapore, with additional offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join

The organization emphasizes creativity, collaboration, curiosity, humility, resilience, and a strong “Always Day 1” mindset. Employees are encouraged to learn, iterate quickly, solve meaningful challenges, and contribute to a fast-growing technology environment where teamwork and innovation matter.

Diversity and Inclusion

The company is committed to building an inclusive workplace where people are respected for their skills, experiences, and perspectives. Its global platform and workforce reflect a wide range of communities, and it aims to foster an environment that celebrates diverse voices.