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AI Data Specialist - Tokyo

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What you’ll work on

Full posting
  • Build and operate data models, pipelines and self-service data products on BigQuery, dbt, Looker and Airflow

  • Develop AI-enabled workflows using LLMs, agents and RAG for performance investigation and campaign planning

  • Automate audience segmentation, campaign performance and UA workflows with Marketing

  • Safeguard data quality and metric consistency across game, marketing and executive reporting

  • Create reusable internal AI tools and documentation for non-technical teams

From the employer’s posting
Build and operate scalable data models, pipelines, semantic layers, and self-service data products using BigQuery, dbt, Looker, Airflow, and related cloud technologies.
Develop production-quality AI-enabled workflows using technologies such as LLMs, agents, retrieval-augmented generation (RAG) knowledge systems
Partner with Marketing to improve and automate workflows for audience segmentation, campaign performance, UA governance and execution
Safeguard data quality and metric consistency across game, marketing, and executive reporting
Create reusable internal tools, patterns, and documentation that make AI accessible to non-technical teams

What you’ll bring

All qualifications

Core experience

  • 5+ years of experience in data engineering, analytics engineering, machine learning engineering, or a closely related role.
  • Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting.
  • Hands-on experience building AI solutions for real business workflows, including LLM applications, AI agents, Model Context Protocol (MCP) or similar tool-integration layers, retrieval-augmented generation (RAG), prompt and tool orchestration, and model evaluation.
  • Experience building tools for and working directly with Product, LiveOps, Marketing, User Acquisition (UA), CRM, or Game Operations teams, with the ability to identify and prioritize high-impact opportunities and translate ambiguous business and operational needs into durable technical systems that teams can trust and reuse.
  • Experience building reusable internal data and AI tools and driving adoption among technical and non-technical users through documentation, training, and hands-on enablement, while contributing to AI operating models through shared standards, governance, ownership, and review practices across functions and regions.
  • Ability to work from Scopely Explore’s Tokyo office three days per week.
Qualification wording
5+ years of experience in data engineering, analytics engineering, machine learning engineering, or a closely related role.
Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting.
Hands-on experience building AI solutions for real business workflows, including LLM applications, AI agents, Model Context Protocol (MCP) or similar tool-integration layers, retrieval-augmented generation (RAG), prompt and tool orchestration, and model evaluation.
Experience building tools for and working directly with Product, LiveOps, Marketing, User Acquisition (UA), CRM, or Game Operations teams, with the ability to identify and prioritize high-impact opportunities and translate ambiguous business and operational needs into durable technical systems that teams can trust and reuse.
Experience building reusable internal data and AI tools and driving adoption among technical and non-technical users through documentation, training, and hands-on enablement, while contributing to AI operating models through shared standards, governance, ownership, and review practices across functions and regions.
Ability to work from Scopely Explore’s Tokyo office three days per week.

About Scopely

Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play.

In the employer’s words · Read in context

Apply at Scopely

Posting record

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Status in our records
Live
First seen by us
Aug 26, 202670 days ago
Recorded sightings
102
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 70

Up longer than most. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Scopely is hiring

9 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • BigQuery
  • dbt
  • Looker
  • Snowflake
  • Airflow
Where the posting names them
- Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting. - Exceptional SQL skills and strong data-modeling fundamentals, including dimensional modeling, metric design, semantic layers, and scalable analytical data products, along with strong ability to write clean, maintainable production code for pipelines, automation, integrations, and AI-enabled workflows. - Hands-on experience building AI solutions for real business workflows, including LLM applications, AI agents, Model Context Protocol (MCP) or similar tool-integration layers, retrieval-augmented generation (RAG), prompt and tool orchestration, and model evaluation.
- Partner cross-functionally with stakeholders across Product, LiveOps, Marketing, User Acquisition (UA), CRM, and Game Operations (including product managers, marketers, analysts, data scientists, engineers, and studio leadership) to identify and prioritize high-impact data and automation opportunities and translate ambiguous business needs into reliable AI-native technical systems. - Build and operate scalable data models, pipelines, semantic layers, and self-service data products using BigQuery, dbt, Looker, Airflow, and related cloud technologies. - Develop production-quality AI-enabled workflows using technologies such as LLMs, agents, retrieval-augmented generation (RAG) knowledge systems, evaluation frameworks, and human-in-the-loop review patterns to help teams investigate performance, detect anomalies, prepare decision briefs, and plan and evaluate campaigns.
- 5+ years of experience in data engineering, analytics engineering, machine learning engineering, or a closely related role. - Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting. - Exceptional SQL skills and strong data-modeling fundamentals, including dimensional modeling, metric design, semantic layers, and scalable analytical data products, along with strong ability to write clean, maintainable production code for pipelines, automation, integrations, and AI-enabled workflows.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Scopely Explore is seeking a highly motivated AI Data Specialist/ Engineer to join our Tokyo Studio, supporting Monster Hunter Now and Pikmin Bloom. This role will sit at the intersection of data engineering, AI tooling, marketing, live game operations, and product strategy.

Scopely Explore’s Tokyo Studio builds games that inspire people to explore the real world together. Monster Hunter Now brings players outside to hunt, craft, and grow stronger together, while Pikmin Bloom helps people find joy in everyday walking and real-world memories. As an AI Data Engineer, you will build the trusted data pipelines, AI-native tools, and automation systems that help our teams operate these games with more speed, rigor, and creativity.

 

Responsibilities

  • Partner cross-functionally with stakeholders across Product, LiveOps, Marketing, User Acquisition (UA), CRM, and Game Operations (including product managers, marketers, analysts, data scientists, engineers, and studio leadership) to identify and prioritize high-impact data and automation opportunities and translate ambiguous business needs into reliable AI-native technical systems.
  • Build and operate scalable data models, pipelines, semantic layers, and self-service data products using BigQuery, dbt, Looker, Airflow, and related cloud technologies.
  • Develop production-quality AI-enabled workflows using technologies such as LLMs, agents, retrieval-augmented generation (RAG) knowledge systems, evaluation frameworks, and human-in-the-loop review patterns to help teams investigate performance, detect anomalies, prepare decision briefs, and plan and evaluate campaigns.
  • Partner with Marketing to improve and automate workflows for audience segmentation, campaign performance, UA governance and execution, reactivation, event planning, and post-launch analysis.
  • Safeguard data quality and metric consistency across game, marketing, and executive reporting while promoting responsible AI use through appropriate evaluation, oversight, and human review.
  • Create reusable internal tools, patterns, and documentation that make AI accessible to non-technical teams while preserving trust, reviewability, and clear source-of-truth data. Contribute hands-on to Tokyo Studio’s broader AI operating model and help teams adopt effective AI-enabled workflows.
  • Use AI-assisted engineering tools responsibly by validating generated code and analysis through rigorous review, automated testing, and established quality gates (including linting, type checking, and CI) before production.

 

Qualifications

  • 5+ years of experience in data engineering, analytics engineering, machine learning engineering, or a closely related role.
  • Deep expertise designing, building, deploying, and operating production data platforms across cloud data warehousing (e.g., BigQuery or Snowflake), data transformation and modeling (e.g., dbt), business intelligence and semantic layers (e.g., Looker), and workflow orchestration (e.g., Airflow), with demonstrated ownership of reliability, observability, data quality, performance, cost efficiency, and production troubleshooting.
  • Exceptional SQL skills and strong data-modeling fundamentals, including dimensional modeling, metric design, semantic layers, and scalable analytical data products, along with strong ability to write clean, maintainable production code for pipelines, automation, integrations, and AI-enabled workflows.
  • Hands-on experience building AI solutions for real business workflows, including LLM applications, AI agents, Model Context Protocol (MCP) or similar tool-integration layers, retrieval-augmented generation (RAG), prompt and tool orchestration, and model evaluation.
  • Strong judgment and hands-on experience establishing data-quality controls, consistent metric definitions, and responsible AI practices across data and AI-enabled systems (including reliability, privacy, access control, explainability, evaluation, and human review) and validating AI-generated code and analysis through code review and automated testing.
  • Experience building tools for and working directly with Product, LiveOps, Marketing, User Acquisition (UA), CRM, or Game Operations teams, with the ability to identify and prioritize high-impact opportunities and translate ambiguous business and operational needs into durable technical systems that teams can trust and reuse.
  • Experience building reusable internal data and AI tools and driving adoption among technical and non-technical users through documentation, training, and hands-on enablement, while contributing to AI operating models through shared standards, governance, ownership, and review practices across functions and regions.
  • Excellent business-level verbal and written communication in both English and Japanese.
  • Ability to work from Scopely Explore’s Tokyo office three days per week.

 

Plus If...

  • You enjoy helping teams become more capable by building practical systems that combine better tools, trusted data, and thoughtful automation to support faster, better-informed decisions.
  • You are passionate about games and player behavior, have experience with free-to-play mobile, live-service, or location-based products, and are familiar with real-world or social mobile games such as Monster Hunter Now, Pikmin Bloom, or Pokémon GO.
  • You have experience modernizing prototype or locally operated data workflows into reliable, scalable, cloud-managed production systems.

 

About Scopely

Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play.

Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come.

Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play.

Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/. 

Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official website and verify that all Talent Partner communications come from an email address ending in @scopely.com.

Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice.

Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

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JP - Tokyo, Japan

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