2 days ago

Data Product Manager, AI Data Platform

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Own and evolve the data infrastructure layer for an AI data annotation platform, defining the product vision for data pipelines, data quality frameworks, RBAC governance, and scalable data delivery. Translate complex labeling needs into secure, standardized data products, working hands-on with schema design, pipeline orchestration, and ETL/ELT workflows. Drive roadmap and metrics governance, ensure SLA and reliability through DQC and root-cause analysis, and partner with Engineering, Ops, QA, and Platform PM to deliver data readiness at scale.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Product Management

Seniority: Mid level

Key Responsibilities

•Own the product strategy and roadmap for data infrastructure, including ingestion, transformation, DQC, delivery pipelines, and metric governance.
•Define data asset standards such as unified metric dictionaries, pipeline coding templates, and data quality SLAs.
•Design and drive RBAC governance for data assets to ensure compliance and security across teams.
•Translate labeling business requirements into pipeline specifications and work with engineers to build and maintain ETL/ELT workflows.
•Monitor pipeline reliability, throughput, and SLA adherence; lead root-cause analysis and continuous improvement while partnering cross-functionally for data readiness.

Key Requirements

•3+ years of data engineering or data platform experience, with at least 1 year in product management or product ownership.
•Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
•Proficiency in SQL (Hive/Spark SQL) and working knowledge of Python for data processing and automation.
•Hands-on experience with data pipeline tools (Airflow, Spark, Flink) and ETL/ELT design patterns.
•Experience with data governance including RBAC, data quality monitoring, SLA management, and data lineage.

Experience:3+ yearsData engineeringData platforms

Education:

Skills:Analytical thinkingCross-functional influencePRD writing

Tech Stack:SQLHiveSpark SQLPythonAirflowSparkFlinkETLELTCSVJSONAPIRBACData quality

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

2 days ago

Data Product Manager, AI Data Platform

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 7 hours agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Product Management

Seniority: Mid level

Key Responsibilities

•Own the product strategy and roadmap for data infrastructure, including ingestion, transformation, DQC, delivery pipelines, and metric governance.
•Define data asset standards such as unified metric dictionaries, pipeline coding templates, and data quality SLAs.
•Design and drive RBAC governance for data assets to ensure compliance and security across teams.
•Translate labeling business requirements into pipeline specifications and work with engineers to build and maintain ETL/ELT workflows.
•Monitor pipeline reliability, throughput, and SLA adherence; lead root-cause analysis and continuous improvement while partnering cross-functionally for data readiness.

Key Requirements

•3+ years of data engineering or data platform experience, with at least 1 year in product management or product ownership.
•Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
•Proficiency in SQL (Hive/Spark SQL) and working knowledge of Python for data processing and automation.
•Hands-on experience with data pipeline tools (Airflow, Spark, Flink) and ETL/ELT design patterns.
•Experience with data governance including RBAC, data quality monitoring, SLA management, and data lineage.

Experience:3+ yearsData engineeringData platforms

Education:

Skills:Analytical thinkingCross-functional influencePRD writing

Tech Stack:SQLHiveSpark SQLPythonAirflowSparkFlinkETLELTCSVJSONAPIRBACData quality

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn