Head of Data
1. About the Company<\/span>
<\/h2>Puzzle Studio is a fast\-growing mobile game studio with a mission to create fun, creative, and high\-quality puzzle games for players around the world.<\/span>
<\/p>We are guided by our core values of Determination, Dedication, Continuous Learning, Proactivity, and Collaboration, which shape how we work and grow together. At Puzzle Studio, we aim to deliver gaming experiences that bring joy and relaxation to our players.<\/span>
<\/p>If you are passionate about gaming, eager to learn, and excited to turn creative ideas into reality, we\u2019d love to have you on our team.<\/span>
<\/p>2. Overview<\/span>
<\/h2>We are looking for a Head of Data to lead the Data & BI Team, reporting directly to the CEO and Board of Directors (BOD) and managing the Data Engineering (DE) and Data Analytics (DA) teams.<\/span>
<\/p>Puzzle Studio is a fast\-growing mobile game studio developing and publishing casual and puzzle games for global players. Our business operates across multiple user acquisition channels, including Direct UA and MCPE/Reward, together with advertising monetization (AppLovin MAX) and in\-app purchases (IAP). Business decisions across campaign scaling, LTV:CAC optimization, fraud detection, and product optimization are all driven by data.<\/span>
<\/p>As the company continues building its Single Source of Truth (SSOT) data platform, all operational data is being centralized into a unified data warehouse (ClickHouse), standardized through multiple layers from Raw, Staging, Mart, Cohort, to KPI, and governed by a centralized Semantic Layer where business metrics are consistently defined across the organization. Our long\-term vision is to evolve from traditional dashboards into an AI\-powered Decision Intelligence Platform, enabling natural language analytics through AI technologies such as WrenAI and Large Language Models (LLMs).<\/span>
<\/p>As the owner of this vision, the Head of Data is responsible for ensuring that data becomes the company's single, trusted source of truth, empowering teams across Executive Management, User Acquisition, Product, Ad Monetization, and Finance to make faster, more accurate, and data\-driven decisions.<\/span>
<\/p>3. Key Responsibilities<\/span>
<\/h2>3.1. Data Strategy & Single Source of Truth (SSOT)<\/span>
<\/h3>Develop and own the company's data roadmap, aligning Company OKRs with Strategic Initiatives (STR) and Jira Epics, while regularly reviewing and adjusting priorities based on business needs.<\/span>
<\/p><\/li>Establish and govern the company's Single Source of Truth (SSOT), including defining official data sources for each business domain, enforcing the principle of no direct KPI overrides in dashboards, and managing the KPI definition change process.<\/span>
<\/p><\/li>Serve as the Directly Responsible Individual (DRI) for resolving data discrepancies and ensuring a single source of truth across all teams.<\/span>
<\/p><\/li><\/ul>3.2. Data Architecture & Platform<\/span>
<\/h3>Own the company's BI infrastructure architecture, covering the entire data flow from Data Sources → AWS (collection, validation, routing) → ClickHouse Data Warehouse (Raw, Staging, Mart, Cohort, KPI) → Semantic Layer → Reporting → AI Analytics.<\/span>
<\/p><\/li>Ensure data pipelines (Airflow, ETL/ELT) operate reliably with monitoring, data quality controls (missing, duplicate, invalid data), and backup & recovery mechanisms.<\/span>
<\/p><\/li>Define the infrastructure strategy to optimize query performance, cloud costs, and scalability as the number of games and data volume continue to grow.<\/span>
<\/p><\/li><\/ul>3.3. Semantic Layer & KPI Governance<\/span>
<\/h3>Own the Semantic Layer, the core foundation of the data platform, by defining standardized cohort models (D0, D1, D7, D30, D90) and key business KPIs including LTV, CAC, ROAS, Retention, ARPPU, and ARPDAU.<\/span>
<\/p><\/li>Develop and maintain the company's KPI Dictionary, Business Glossary, Formula Catalog, and Threshold Framework as standardized references across the organization.<\/span>
<\/p><\/li>Own and govern business decision engines, including the Headroom Engine, Campaign Scoring, D7\-to\-D90 Proxy Analysis, and Cheat Metrics.<\/span>
<\/p><\/li><\/ul>3.4. Business Decision Support<\/span>
<\/h3>Support User Acquisition (Direct UA and MCPE) by building lifetime cohort\-based LTV:CAC frameworks, distinguishing Direct fixed CAC from MCPE cumulative CAC, and providing headroom analysis and campaign classification to support campaign scaling and bidding decisions.<\/span>
<\/p><\/li>Support Product teams by analyzing retention, churn, level progression, feature adoption, and user journeys, focusing on identifying root causes rather than simply reporting metrics.<\/span>
<\/p><\/li>Support Ad Monetization through analysis of ARPDAU, eCPM, waterfall and floor optimization, and ad placement performance across Rewarded, Interstitial, and Banner formats.<\/span>
<\/p><\/li>Lead anti\-cheat analytics by identifying fake installs, fraudulent IAP activities, and bot traffic while quantifying fraud costs for bidding optimization.<\/span>
<\/p><\/li>Provide Executive Management and Finance with executive dashboards, P&L reporting, profitability analysis, and unit economics aligned with the company's North Star metrics.<\/span>
<\/p><\/li><\/ul>3.5. AI Analytics (Future Direction)<\/span>
<\/h3>Lead the roadmap from ClickHouse → Semantic Layer → WrenAI → LLMs (Claude/GPT) → Chat Interface, enabling natural language access to business KPIs and insights.<\/span>
<\/p><\/li>Establish AI security principles by ensuring AI models only access the Semantic Layer rather than raw data, while developing an RCA (Root Cause Analysis) Library and internal knowledge base to support AI\-driven insights.<\/span>
<\/p><\/li><\/ul>3.6. Team Leadership & Development<\/span>
<\/h3>Lead, recruit, and develop the Data Engineering and Data Analytics teams, with clear ownership between infrastructure & pipelines (DE) and business logic & semantic modeling (DA).<\/span>
<\/p><\/li>Manage Agile delivery processes including sprint planning, sprint reviews, story point estimation, backlog prioritization, and BI request tracking.<\/span>
<\/p><\/li>Promote self\-service analytics to reduce dependencies between Data Engineering and Data Analytics while standardizing onboarding processes and technical documentation.<\/span>
<\/p><\/li><\/ul><\/span>
Yêu cầu<\/h3>4. Requirements<\/span>
<\/h2>Must Have<\/span>
<\/h3>At least 5 years of experience in Data, Business Intelligence, or Analytics, including a minimum of 2 years in a team leadership or management role overseeing Data Engineering and/or Data Analytics teams.<\/span>
<\/p><\/li>Strong experience designing and implementing layered data warehouse architectures and Single Source of Truth (SSOT) frameworks, including Semantic Layer and KPI governance.<\/span>
<\/p><\/li>Proficiency in SQL and data modeling (fact tables, dimension tables, cohort analysis), with hands\-on experience using cloud data warehouses (ClickHouse is a strong advantage) and orchestration tools such as Airflow.<\/span>
<\/p><\/li>Solid understanding of end\-to\-end data pipelines, including data ingestion (API and file synchronization), ETL/ELT processes, data quality management, and monitoring.<\/span>
<\/p><\/li>Strong business acumen with deep knowledge of unit economics, including LTV, CAC, ROAS, ARPDAU, and retention, and the ability to translate data into business decisions.<\/span>
<\/p><\/li>Excellent leadership, communication, and cross\-functional collaboration skills, with experience working closely with User Acquisition, Product, Finance, and Executive teams.<\/span>
<\/p><\/li><\/ul>Nice to Have<\/span>
<\/h3>Experience in the mobile gaming industry, particularly in casual games, User Acquisition, and ad monetization.<\/span>
<\/p><\/li>Hands\-on experience with platforms such as Singular, AppLovin MAX, GameAnalytics, RevenueCat, and MCPE/Reward networks including Tapjoy and AyeT.<\/span>
<\/p><\/li>Experience designing or implementing anti\-cheat and fraud detection solutions for User Acquisition traffic.<\/span>
<\/p><\/li>Experience with AI\-powered analytics, Large Language Models (LLMs), Retrieval\-Augmented Generation (RAG), and semantic search solutions such as WrenAI or similar technologies.<\/span>
<\/p><\/li>Programming experience in Python or Rust for building internal tools, user\-defined functions (UDFs), forecasting models, or data automation.<\/span>
<\/p><\/li><\/ul>Core Competencies<\/span>
<\/h3>Strong ownership and accountability, with the confidence to act as the Directly Responsible Individual (DRI) and ensure the reliability and integrity of company\-wide data.<\/span>
<\/p><\/li>Systems thinking, with the ability to design scalable, sustainable, and maintainable data platforms rather than temporary solutions.<\/span>
<\/p><\/li>Pragmatic and outcome\-driven mindset, prioritizing measurable business outcomes over outputs while making decisions based on testable hypotheses.<\/span>
<\/p><\/li>Excellent communication skills, with the ability to translate complex technical data into actionable business insights for non\-technical stakeholders.<\/span>
<\/p><\/li><\/ul>5. Success Outcomes (First 6\u201312 Months)<\/span>
<\/h2>Within the first 6\u201312 months, the successful candidate is expected to achieve the following outcomes:<\/span>
<\/p>Single Source of Truth (SSOT) & Semantic Layer: Establish and operationalize a unified KPI Dictionary, ensuring all official dashboards are built on a single, standardized data source.<\/span>
<\/p><\/li>Unified KPI Datasources: Standardize and automate cohort reporting (D0\u2013D90) together with core business metrics, including LTV, CAC, ROAS, and Retention.<\/span>
<\/p><\/li>Data Reliability: Achieve over 95% data quality coverage by implementing comprehensive pipeline monitoring, automated alerts, and robust data quality controls.<\/span>
<\/p><\/li>Business Impact: Reduce dependency on manual spreadsheets while improving the accuracy of D7\-to\-D90 forecasting, enabling faster and more reliable business decision\-making.<\/span>
<\/p><\/li>AI Analytics: Deliver an MVP AI Copilot that enables users to query business KPIs through the Semantic Layer using natural language.<\/span>
<\/p><\/li>Team Development: Build a high\-performing Data organization with clear ownership between Data Engineering and Data Analytics teams, supported by stable Agile processes and consistent sprint execution.<\/span>
<\/p><\/li><\/ul><\/span>
Đãi ngộ<\/h3>6. What We Offer<\/span>
<\/h2>Competitive salary package with performance and salary reviews twice per year.<\/span>
<\/p><\/li>Quarterly performance bonuses.<\/span>
<\/p><\/li>A flexible, open, and collaborative working environment where ownership and initiative are valued.<\/span>
<\/p><\/li>Opportunity to work directly on global mobile game products with strong growth potential.<\/span>
<\/p><\/li>A team culture that encourages learning, experimentation, and continuous improvement.<\/span>
<\/p><\/li>Comfortable pantry with coffee, tea, snacks, and occasional afternoon treats.<\/span>
<\/p><\/li>Fun and friendly office activities including board games, foosball, weekly football, and badminton sessions.<\/span>
<\/p><\/li>Clear long\-term growth opportunities with a transparent vision and development roadmap.<\/span>
<\/p><\/li>Direct collaboration with passionate teammates who love games and enjoy building products together.<\/span>
<\/p><\/li><\/ul><\/span>
<\/p>
We are guided by our core values of Determination, Dedication, Continuous Learning, Proactivity, and Collaboration, which shape how we work and grow together. At Puzzle Studio, we aim to deliver gaming experiences that bring joy and relaxation to our players.<\/span> If you are passionate about gaming, eager to learn, and excited to turn creative ideas into reality, we\u2019d love to have you on our team.<\/span> We are looking for a Head of Data to lead the Data & BI Team, reporting directly to the CEO and Board of Directors (BOD) and managing the Data Engineering (DE) and Data Analytics (DA) teams.<\/span> Puzzle Studio is a fast\-growing mobile game studio developing and publishing casual and puzzle games for global players. Our business operates across multiple user acquisition channels, including Direct UA and MCPE/Reward, together with advertising monetization (AppLovin MAX) and in\-app purchases (IAP). Business decisions across campaign scaling, LTV:CAC optimization, fraud detection, and product optimization are all driven by data.<\/span> As the company continues building its Single Source of Truth (SSOT) data platform, all operational data is being centralized into a unified data warehouse (ClickHouse), standardized through multiple layers from Raw, Staging, Mart, Cohort, to KPI, and governed by a centralized Semantic Layer where business metrics are consistently defined across the organization. Our long\-term vision is to evolve from traditional dashboards into an AI\-powered Decision Intelligence Platform, enabling natural language analytics through AI technologies such as WrenAI and Large Language Models (LLMs).<\/span> As the owner of this vision, the Head of Data is responsible for ensuring that data becomes the company's single, trusted source of truth, empowering teams across Executive Management, User Acquisition, Product, Ad Monetization, and Finance to make faster, more accurate, and data\-driven decisions.<\/span> Develop and own the company's data roadmap, aligning Company OKRs with Strategic Initiatives (STR) and Jira Epics, while regularly reviewing and adjusting priorities based on business needs.<\/span> Establish and govern the company's Single Source of Truth (SSOT), including defining official data sources for each business domain, enforcing the principle of no direct KPI overrides in dashboards, and managing the KPI definition change process.<\/span> Serve as the Directly Responsible Individual (DRI) for resolving data discrepancies and ensuring a single source of truth across all teams.<\/span> Own the company's BI infrastructure architecture, covering the entire data flow from Data Sources → AWS (collection, validation, routing) → ClickHouse Data Warehouse (Raw, Staging, Mart, Cohort, KPI) → Semantic Layer → Reporting → AI Analytics.<\/span> Ensure data pipelines (Airflow, ETL/ELT) operate reliably with monitoring, data quality controls (missing, duplicate, invalid data), and backup & recovery mechanisms.<\/span> Define the infrastructure strategy to optimize query performance, cloud costs, and scalability as the number of games and data volume continue to grow.<\/span> Own the Semantic Layer, the core foundation of the data platform, by defining standardized cohort models (D0, D1, D7, D30, D90) and key business KPIs including LTV, CAC, ROAS, Retention, ARPPU, and ARPDAU.<\/span> Develop and maintain the company's KPI Dictionary, Business Glossary, Formula Catalog, and Threshold Framework as standardized references across the organization.<\/span> Own and govern business decision engines, including the Headroom Engine, Campaign Scoring, D7\-to\-D90 Proxy Analysis, and Cheat Metrics.<\/span> Support User Acquisition (Direct UA and MCPE) by building lifetime cohort\-based LTV:CAC frameworks, distinguishing Direct fixed CAC from MCPE cumulative CAC, and providing headroom analysis and campaign classification to support campaign scaling and bidding decisions.<\/span> Support Product teams by analyzing retention, churn, level progression, feature adoption, and user journeys, focusing on identifying root causes rather than simply reporting metrics.<\/span> Support Ad Monetization through analysis of ARPDAU, eCPM, waterfall and floor optimization, and ad placement performance across Rewarded, Interstitial, and Banner formats.<\/span> Lead anti\-cheat analytics by identifying fake installs, fraudulent IAP activities, and bot traffic while quantifying fraud costs for bidding optimization.<\/span> Provide Executive Management and Finance with executive dashboards, P&L reporting, profitability analysis, and unit economics aligned with the company's North Star metrics.<\/span> Lead the roadmap from ClickHouse → Semantic Layer → WrenAI → LLMs (Claude/GPT) → Chat Interface, enabling natural language access to business KPIs and insights.<\/span> Establish AI security principles by ensuring AI models only access the Semantic Layer rather than raw data, while developing an RCA (Root Cause Analysis) Library and internal knowledge base to support AI\-driven insights.<\/span> Lead, recruit, and develop the Data Engineering and Data Analytics teams, with clear ownership between infrastructure & pipelines (DE) and business logic & semantic modeling (DA).<\/span> Manage Agile delivery processes including sprint planning, sprint reviews, story point estimation, backlog prioritization, and BI request tracking.<\/span> Promote self\-service analytics to reduce dependencies between Data Engineering and Data Analytics while standardizing onboarding processes and technical documentation.<\/span> At least 5 years of experience in Data, Business Intelligence, or Analytics, including a minimum of 2 years in a team leadership or management role overseeing Data Engineering and/or Data Analytics teams.<\/span> Strong experience designing and implementing layered data warehouse architectures and Single Source of Truth (SSOT) frameworks, including Semantic Layer and KPI governance.<\/span> Proficiency in SQL and data modeling (fact tables, dimension tables, cohort analysis), with hands\-on experience using cloud data warehouses (ClickHouse is a strong advantage) and orchestration tools such as Airflow.<\/span> Solid understanding of end\-to\-end data pipelines, including data ingestion (API and file synchronization), ETL/ELT processes, data quality management, and monitoring.<\/span> Strong business acumen with deep knowledge of unit economics, including LTV, CAC, ROAS, ARPDAU, and retention, and the ability to translate data into business decisions.<\/span> Excellent leadership, communication, and cross\-functional collaboration skills, with experience working closely with User Acquisition, Product, Finance, and Executive teams.<\/span> Experience in the mobile gaming industry, particularly in casual games, User Acquisition, and ad monetization.<\/span> Hands\-on experience with platforms such as Singular, AppLovin MAX, GameAnalytics, RevenueCat, and MCPE/Reward networks including Tapjoy and AyeT.<\/span> Experience designing or implementing anti\-cheat and fraud detection solutions for User Acquisition traffic.<\/span> Experience with AI\-powered analytics, Large Language Models (LLMs), Retrieval\-Augmented Generation (RAG), and semantic search solutions such as WrenAI or similar technologies.<\/span> Programming experience in Python or Rust for building internal tools, user\-defined functions (UDFs), forecasting models, or data automation.<\/span> Strong ownership and accountability, with the confidence to act as the Directly Responsible Individual (DRI) and ensure the reliability and integrity of company\-wide data.<\/span> Systems thinking, with the ability to design scalable, sustainable, and maintainable data platforms rather than temporary solutions.<\/span> Pragmatic and outcome\-driven mindset, prioritizing measurable business outcomes over outputs while making decisions based on testable hypotheses.<\/span> Excellent communication skills, with the ability to translate complex technical data into actionable business insights for non\-technical stakeholders.<\/span> Within the first 6\u201312 months, the successful candidate is expected to achieve the following outcomes:<\/span> Single Source of Truth (SSOT) & Semantic Layer: Establish and operationalize a unified KPI Dictionary, ensuring all official dashboards are built on a single, standardized data source.<\/span> Unified KPI Datasources: Standardize and automate cohort reporting (D0\u2013D90) together with core business metrics, including LTV, CAC, ROAS, and Retention.<\/span> Data Reliability: Achieve over 95% data quality coverage by implementing comprehensive pipeline monitoring, automated alerts, and robust data quality controls.<\/span> Business Impact: Reduce dependency on manual spreadsheets while improving the accuracy of D7\-to\-D90 forecasting, enabling faster and more reliable business decision\-making.<\/span> AI Analytics: Deliver an MVP AI Copilot that enables users to query business KPIs through the Semantic Layer using natural language.<\/span> Team Development: Build a high\-performing Data organization with clear ownership between Data Engineering and Data Analytics teams, supported by stable Agile processes and consistent sprint execution.<\/span> Competitive salary package with performance and salary reviews twice per year.<\/span> Quarterly performance bonuses.<\/span> A flexible, open, and collaborative working environment where ownership and initiative are valued.<\/span> Opportunity to work directly on global mobile game products with strong growth potential.<\/span> A team culture that encourages learning, experimentation, and continuous improvement.<\/span> Comfortable pantry with coffee, tea, snacks, and occasional afternoon treats.<\/span> Fun and friendly office activities including board games, foosball, weekly football, and badminton sessions.<\/span> Clear long\-term growth opportunities with a transparent vision and development roadmap.<\/span> Direct collaboration with passionate teammates who love games and enjoy building products together.<\/span>
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<\/p>2. Overview<\/span>
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<\/p>3. Key Responsibilities<\/span>
<\/h2>3.1. Data Strategy & Single Source of Truth (SSOT)<\/span>
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<\/p><\/li><\/ul>3.2. Data Architecture & Platform<\/span>
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<\/p><\/li><\/ul>3.3. Semantic Layer & KPI Governance<\/span>
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<\/p><\/li><\/ul>3.4. Business Decision Support<\/span>
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<\/p><\/li><\/ul>3.5. AI Analytics (Future Direction)<\/span>
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<\/p><\/li><\/ul>3.6. Team Leadership & Development<\/span>
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<\/p><\/li><\/ul><\/span>Yêu cầu<\/h3>
4. Requirements<\/span>
<\/h2>Must Have<\/span>
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<\/p><\/li><\/ul>Nice to Have<\/span>
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<\/p><\/li><\/ul>Core Competencies<\/span>
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<\/p><\/li><\/ul>5. Success Outcomes (First 6\u201312 Months)<\/span>
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<\/p><\/li><\/ul><\/span>Đãi ngộ<\/h3>
6. What We Offer<\/span>
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