About Appier 

Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

About the role

We're looking for an experienced data engineer to build and scale our data infrastructure. You'll work on mission-critical systems that power our data-driven decision making, designing robust pipelines and optimizing distributed platforms that process massive datasets.

Responsibilities

• Design, develop, and maintain production data pipelines processing hundreds of terabytes of data daily across distributed systems
• Build, manage, and optimize large-scale data platforms including Spark clusters, Kafka clusters, and related big data infrastructure
• Develop and operate data warehouse systems and ETL pipelines for data collection, processing, storage, and analytics
• Profile and tune performance of critical components to optimize throughput, reduce latency, and improve resource efficiency
• Establish architectural foundations and engineering best practices for the platform
• Design frameworks and tooling to streamline software development, deployment, monitoring, and observability
• Provide technical expertise and guidance on big data system design, performance optimization, and scalability challenges

About you

[Minimum qualifications]

• BS/MS degree in Computer Science or related technical field
• 2+ years of hands-on experience building and operating large-scale distributed systems
• Proficiency in Java and/or Scala for production-level development
• Proven experience building ETL pipelines and data processing workflows using Apache Spark
• Experience managing and optimizing data lakes or data warehouses at scale
• Ability to work independently and adapt quickly in fast-paced, dynamic environments
• Self-motivated learner who takes ownership, manages multiple priorities effectively, and thrives in collaborative team settings
• Experience deploying and managing infrastructure on public cloud platforms (AWS, GCP, or Azure)

[Preferred qualifications]

• Proficiency in Python and/or Golang for building production systems
• Experience profiling and optimizing JVM performance for high-throughput applications
• Hands-on experience managing and operating data platforms such as Hadoop, Kafka, Flink, Hive, Trino, Presto, or ClickHouse
• Knowledge of modern open table formats including Apache Iceberg, Delta Lake, or Hudi 
• Active contributions to open source projects (please include your GitHub profile if applicable)

#LI-AK1

経験レベル
ジュニアからシニア

雇用形態
フルタイム (1日8時間)

上司
テクニカルディレクター

部署
PlayStation Studios Team ASOBI / テクノロジーチーム

勤務場所
東京エリア

About Team ASOBI
Team ASOBIは、東京に拠点を置くPlayStationのファーストパーティスタジオで、PS5向けの大ヒット作『ASTRO BOT』を手掛けたチームです。遊び心にあふれたスタジオで、情熱を持った優れた才能たちが、協力しながら素晴らしい作品を生み出しています。今後も世界中から新たな才能を迎え入れ、さらなる成長を目指しています。Team ASOBIの使命は、すべてのプレイヤーが楽しめる、高品質で革新的なゲーム体験をPlayStationで提供することです。   

▪️詳しい情報はPlayStation Blogをご覧ください！  https://blog.ja.playstation.com/2024/09/05/20240905-astrobot/ 

Role overview
チームが最大限の力を発揮できるよう快適な開発環境を構築し、維持することはタイトル開発プロセスにおいて非常に重要な要素となっています。開発機材の選定や保守、ビルド環境やデータ管理の改善など開発環境の構築を技術面からサポートしていただきます。  

Responsibility

• 開発機材の選定、管理、導入と更新の計画を行います
  
• オフィスと倉庫の機材を管理し、整頓された状態を保ちます 
• 社内ＩＴチームと連携し、サーバ構築やメンテナンスの計画を行います 
• 開発環境全体を把握し、メンバー加入時や更新時のセットアップをサポートします
• 開発機材やＩＴ周りのトラブルに対応します
• 開発イテレーション（コード変更・ビルド・テスト・リリースとデータ共有）における問題点を把握し改善を行います 

求める経験とスキル

• IT関連業務の経験（３年以上）
• Git, Perforce, Jenkins等ゲーム開発環境で利用されるソフトウェアの運用経験
• PCやモニタなどの開発機材やゲーミングデバイスに関するトレンドの把握
• Linux・Windowsサーバ, クラウドサービスの基本的な知識
• Python, PowerShell等での自動化のためのスクリプト開発経験
• 制作ツール開発の経験 (C++, C#, Maya Python)があれば尚可
• ゲームランタイムの実装経験があれば尚可
• チームからニーズを集めるための優れたコミュニケーションスキル
• 議論を効率的に進めるための積極的なコミュニケーション
• 仕事の質を自己評価する能力
• 英語の学習意欲のある方を歓迎（英会話レッスンを受講可能） 

About Team ASOBI
Team ASOBI is a first-party PlayStation Studio located in Tokyo, Japan, responsible for the critically acclaimed ASTRO BOT for PS5. The team is looking to expand by bringing worldwide talents with high skills, passion, and a playful, collaborative mind.  The Studio has a mission to create top quality, innovative games for players of all ages on PlayStation.
Want to learn more? Head over to the PlayStation Blog: PlayStation Blog .

Role overview
Creating and maintaining a well-functioning development environment that allows the team to reach their full potential is a crucial part of our game development process. You will provide technical support for the construction of our development environment, including the selection and maintenance of equipment, as well as the improvement of our build environment and data management process.

Responsibilities

• Select, manage, set up, and plan updates of development equipment.
  
• Manage office and warehouse equipment and maintain an organized state. 
• Work with the internal IT team on server builds and maintenance plans.
• Understand the entire development environment to give support when new members join the studio and when updates take place.
• Respond to problems related to development equipment and IT.
• Identify and improve issues regarding development iterations (code changes, builds, tests, releases, and data sharing) 

Required Skill and Experience 

• IT-related work experience (3 years or more) 
• Experience with software used in game development such as Git, Perforce, Jenkins, etc. 
• Understanding of trends in development equipment such as PCs, monitors, and gaming devices. 
• Basic knowledge of Linux/Windows servers and cloud services. 
• Experience developing scripts for automation in Python, PowerShell, etc. 
• Experience in production tools development (C++, C#, Maya Python) is a plus. 
• Experience implementing game runtimes is a plus. 
• Excellent communication skills to gather needs from the team. 
• Proactive communication to facilitate discussions effectively. 
• Ability to self-evaluate quality of work. 

Language proficiency

• Basic Japanese language skill is required alongside desire to improve (lessons will be provided and paid for). 

「Team ASOBI」
https://www.teamasobi.com/jp/ 

This role requires a strong blend of technical expertise, customer-facing acumen, and solution-oriented problem solving. The Data AS Consultant will work closely with Sales & Account Managers to provide technical leadership and solution design for highly consultative enterprise projects. It is a revenue-generating pre-sales position focused on enabling technical adoption and driving customer success for both new and expansion opportunities.

This role reports directly to the Team Manager, DSI, with a dotted line to the Regional Head of Japan.

Responsibilities

Technical Consultation & Solution Design

• Serve as a trusted technical advisor to enterprise customers, translating business goals into scalable, production-grade technical architectures.
  
  
• Design and document data integration architectures leveraging Similarweb’s APIs, DaaS feeds, and platform products to meet enterprise data requirements.
  
  
• Architect end-to-end data delivery pipelines into client ecosystems (e.g., Snowflake, Databricks, S3, or Google Cloud Platform).
  
  
• Provide technical workshops and POCs, guiding clients on ingestion, normalization, and querying best practices.
  
  
• Develop Statements of Work (SOWs), technical proposals, and detailed integration documentation to accelerate collaboration between internal teams and customers.
  
  

Technical Skill Execution Examples

1. Integration & Data Delivery
   
   
• Role: Design and implement integration workflows delivering Similarweb’s data via API, S3, Snowflake, or GCP Storage, tailored to customer infrastructure.
  
  
• Technical Skills:
  
  
• Advanced SQL querying and performance tuning in Databricks / Snowflake
  
  
• Proficiency with data file formats (CSV, JSON, Parquet, Delta) and understanding the trade-offs between performance, compression, and schema evolution
  
  
• Strong knowledge of ETL design, data governance, and access control
  
  
• Outcome: Clients understand technical feasibility and best practices for incorporating Similarweb data into their analytical stack.
  
  
2. Data Quality, Coverage, and Scalability
   
   
• Role: Explain how data is collected, validated, deduplicated, and scaled across geographies and verticals, referencing internal reruns and benchmarks.
  
  
• Technical Skills: Understanding of data validation, sampling frameworks, distributed storage performance, and data versioning (e.g., Delta Lake advantages).
  
  
• Outcome: Clients gain trust in data quality and scalability across enterprise-grade analytics environments.
  
  
3. Data Sampling & Proof-of-Concept Delivery
   
   
• Role: Generate and deliver custom data samples aligned with client use cases, whether via API queries, Parquet exports, Delta tables, or CSV snapshots.
  
  
• Technical Skills:
  
  
• Hands-on data extraction and transformation using SQL and Python
  
  
• Preparing data in optimal formats (e.g., Parquet v Delta)
  
  
• Managing delivery through multiple mechanisms: secure S3 share, Snowflake Data Share, API endpoints, or CSV download portals.
  
  
• Outcome: Clients can validate data structure, schema, and use-case fit before full-scale adoption.
  
  
4. Use Case Customization & Advanced Analytics
   
   
• Role: Demonstrate how Similarweb data can be enriched with client datasets (POS, CRM, or loyalty).
  
  
• Technical Skills: SQL and Python for data joins, REST and GraphQL APIs, JSON schema design, and familiarity with Model Context Protocol (MCP) for LLM integrations.
  
  
• Outcome: The client sees practical, technically sound pathways to integrating Similarweb data into their own analytical models and AI workflows.
  
  

Collaboration with Sales & Customer Teams

• Partner with Enterprise Sales Managers to qualify and design technical solutions during the sales process.
  
  
• Work with Enterprise Account Managers to drive expansion and deepen platform adoption through technical enablement.
  
  
• Collaborate closely with Customer Success and Delivery teams to ensure smooth technical transitions from pre-sales to production.
  
  
• Create reusable demos, templates, and data delivery playbooks for use across GCR teams.
  
  
• Participate in strategic account planning and contribute feedback to product and data engineering based on customer needs.
  
  

Market & Product Expertise

• Stay up to date with AI/LLM data standards, data engineering best practices, and cloud-native architectures.
  
  
• Provide feedback to product and data engineering on API performance, schema design, and data format optimization.
  
  
• Maintain familiarity with Model Context Protocol (MCP), OpenAPI, and emerging standards for data interoperability and contextual AI integrations.
  
  

Project Support & Technical Governance

• Lead technical scoping and architecture reviews during the pre-sales phase.
  
  
• Oversee sample generation, performance validation, and schema testing.
  
  
• Provide escalation support on data performance, pipeline reliability, and delivery troubleshooting.
  
  
• Ensure solutions align with data security, privacy, and compliance best practices.
  
  

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
  
  
• 5+ years in pre-sales, solution architecture, or data consulting, with a strong focus on technical delivery.
• Technical Expertise:
  
  
• Data Architecture & Integration: Deep understanding of cloud ecosystems (AWS, Azure, GCP) and data warehousing frameworks (Snowflake, Databricks, Redshift).
  
  
• SQL & Data Modeling: Strong query and optimization skills for data analysis and transformation.
  
  
• APIs & Data Exchange: REST and GraphQL API fluency, JSON schema design, authentication (OAuth 2.0, JWT).
  
  
• File Formats: Deep understanding of CSV, JSON, Parquet, and Delta file formats—knowing when to use each for efficiency, scalability, or incremental updates.
  
  
• Data Sample Delivery: Ability to create, test, and deliver sample datasets across APIs, S3, and warehouse sharing mechanisms.
  
  
• MCP & AI Integrations: Awareness of Model Context Protocol, LLM context injection, and structured data retrieval patterns.
  
  
• Proven experience translating business requirements into technical solutions for large enterprise data ecosystems.
  
  
• Excellent communication and presentation skills—able to bridge the gap between technical and commercial teams.
  
  
• Fluent in Japanese and English (written and spoken) with experience serving enterprise clients.
• Strong problem-solving, self-management, and team collaboration skills.

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

About The Role

We’re building agentic and recommendation products that power next-gen digital marketing. You will lead an engineering team at the intersection of ML systems, LLM/agent orchestration, and enterprise SaaS to deliver reliable, measurable outcomes for marketers—faster execution, smarter budget allocation, and differentiated brand performance.

Our goal is to build Marketing Agents (e.g., Audience Agent, Campaign Agent and Insight Agent) and Consumer-Facing Agents (e.g., Service Agent, Sales Agent), underpinned by a One Data Platform that enables trustworthy personalization and decisioning at scale.

What You'll build

Agentic Marketing Automation

• Natural language task assignment: users describe objectives and constraints in plain language; agents plan, execute, and report.
• Amplifying brand advantage: systems that help strong brands compound performance while giving others actionable levers to close gaps.
• One Data Platform integration: unify identity, events, product catalog, and campaign data to drive consistent decisions across products.

[Product Areas]

• Marketing Agents
  • Audience Agent: segmentation, targeting strategies, cohort insights, next-best audience.
  • Campaign Agent: multi-step campaign planning, creative/testing suggestions, launch & iteration, performance diagnosis.
• Consumer-Facing Agents
  • Service Agent: post-purchase journeys, retention, support deflection, cross-sell triggers.
  • Sales Agent: lead qualification, outreach recommendations, pipeline nudges (where applicable).
• Recommendation products: ranking, next-best-action, uplift modeling, personalized content/channel selection.

Responsibilities 

Engineering leadership

• Lead a team of engineers (and partner closely with ML scientists) to deliver enterprise-grade agent and recommendation capabilities.
• Translate product goals into technical strategy, milestones, and execution plans; drive delivery with high quality and predictable cadence. 
• Establish engineering excellence: code quality, testing, observability, incident response, and continuous improvement.
• Build an environment of humble, hungry, smart execution—measure outcomes, iterate quickly, reduce waste.

Agentic Systems & ML Product Delivery

• Design and ship agent frameworks: planning/execution loops, tool calling, memory, retrieval, safety guardrails, and evaluation.
• Define evaluation methodology for agents: offline benchmarks, online experiments, success metrics, and human-in-the-loop review flows.
• Assure solid integration with One Data Platform: data contracts, feature availability, privacy controls, and reliability SLAs.
• Partner with Product, Design, Data/ML, and GTM to ensure model behavior aligns with user needs and business goals.

Stakeholder & Culture

• Drive stakeholder alignment: connect engineering objectives to business outcomes (revenue, retention, customer value).
• Promote an autonomous culture: empower autonomous decision-making for both the team and the systems you build.
• Manage fast-paced experimentation while ensuring security, compliance, and enterprise readiness.

About you 

[Minimum qualifications]

• 8+ years professional experience as a Software Engineer; 4+ years in a management/leadership role.
• Strong communication in English (written and verbal).
• Degree in Computer Science / Informatics or equivalent practical experience.
• Proven track record delivering enterprise-grade products (reliability, security, observability, performance).
• Experience working with or managing engineers and ML scientists.
• Experience delivering solutions using Agile principles.

[Preferred qualifications]

• Experience building LLM/agentic systems in production (tool use, RAG, orchestration, evaluation).
• Hands-on background with ML systems (recommendation, ranking, attribution, uplift, LTV, forecasting) and their productionization.
• Familiarity with data platforms (event pipelines, identity resolution, feature stores, lakehouse/warehouse) and data governance.
• Experience with A/B testing and causal measurement; comfortable making tradeoffs using metrics.
• Exposure to MA/CRM domains: segmentation, journeys, omnichannel messaging, campaign ops, budget pacing.
• Experience in leading hybrid (onsite/remote) engineering team.

About Us (Appier Engineering)
At Appier Engineering, we aim to be humble, hungry and smart. We improve through constant measurement and feedback—building less and talking more to ensure outcomes users love while reducing waste. We innovate by failing well, adapt quickly, and stay efficient and responsive when needed. We’re looking for an Engineering Manager who embodies these values through work and life experiences.

About Appier 

Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

About the role

Appier’s solutions are powered by proprietary deep learning and machine learning technologies to empower every business to use AI to turn data into business insights and decisions. As a Software Engineer, Data Backend, you will be involved in helping to build critical components of this platform.

Responsibilities

• Design, develop, and maintain RESTful APIs using Python.
• Build and manage robust data warehouses utilizing Trino/Presto and Pinot.
• Design and develop data pipelines using Apache Airflow and Apache Spark.
• Work closely with cross-functional teams to develop automation tools that streamline daily operations.
• Implement state-of-the-art monitoring and alerting systems to ensure optimal system performance and stability.
• Address queries from applications in a timely and effective manner, ensuring high client satisfaction.
• Work on cloud platforms such as AWS and GCP, leveraging their capabilities to optimize data operations.
• Utilize Kubernetes (k8s) for container orchestration to facilitate efficient deployment and scaling of applications.

About you

[Minimum qualifications]

• BS/MS degree in Computer Science
• 3+ years of experience in building and operating large-scale distributed systems or applications
• Experience in Kubernetes development, Linux/Unix
• Experience in managing data lake or data warehouse
• Expertise in developing data structures, algorithms on top of Big Data platforms
• Ability to operate effectively and independently in a dynamic, fluid environment
• Ability to work in a fast-moving team environment and juggle many tasks and projects
• Eagerness to change the world in a huge way by being a self-motivated learner and builder

[Preferred qualifications]

• Contributing to open source projects is a huge plus (please include your github link)
• Experience working with Python, Scala/Java is a plus
• Experience with Hadoop, Hive, Flink, Presto/Trino and related big data systems is a plus  
• Experience with Public Cloud like AWS or GCP is a plus 

#LI-AK1