Data Platform Engineer

About VisasQ VisasQ operates one of Japan's largest knowledge platforms, connecting the knowledge of more than 800,000 people across 190 countries under the mission "We make insightful connections possible." We provide a wide variety of knowledge matching services, including interviews, surveys, and hands-on project support, to more than 2,000 clients in Japan and overseas. Following the acquisition of a major U.S. company in 2021, we have expanded to 7 locations worldwide and are accelerating our growth in global markets. As a challenger in the market, we value individual autonomy and team collaboration, and we keep improving our products through trial and error. To realize our mission, we are looking for colleagues who will use the power of technology to circulate knowledge and build a new market together. Recruitment Background VisasQ operates a knowledge platform dedicated to its mission: "We make insightful connections possible." Connecting businesses with precisely the right expertise across 190+ countries and a network of over 800,000 experts, our Global Expert Network Service (ENS) provides high-precision matching across region and language barriers for professional clients, including management consulting firms and financial institutions. In an era where generative AI has made publicly available web information easily accessible, the value of unstructured first-hand human experience and knowledge has grown exponentially. Currently, vast amounts of data continue to accumulate across multiple products and multi-cloud environments (Azure and GCP). However, the precision of AI agents relies fundamentally on the quality of the underlying data. Core elements—such as company master identity resolution, employment history accuracy, and compliance verification reliability—directly impact the quality of AI agent decision-making. While we are incrementally improving data quality within our current structures, we are looking toward building a unified master data platform that consolidates multiple data sources. We are seeking a Data Platform Engineer who can design the data platform architecture that fuels our AI products and lead complex, data-driven design decisions based on empirical evaluation. Responsibilities Lead the entire technical lifecycle of our data foundation—from architectural design supporting search, analytics, and compliance, to entity resolution (deduplication), data cleansing, and building mechanisms for continuous data quality assurance. Data Platform Architectural Design Design data models across multiple products and multi-cloud environments (Azure/GCP) to ensure reliable data supply for AI products, search engines, analytics, and compliance checks. Define Single Source of Truth (SSOT) strategies and integrate confidence scoring into data models based on empirical findings. Entity Resolution & Data Cleansing Pipeline Design and implement multi-stage entity resolution pipelines combining deterministic matching, scoring models, and human-in-the-loop review workflows. Build robust data cleansing processes that enforce idempotency and state rollback capabilities to maintain high data integrity over time. Establish monitoring and anomaly detection mechanisms to ensure stable pipeline operations. Data Quality Research & Problem Solving Investigate data quality issues, identify root causes within data/codebases, and formulate impactful technical solutions based on business metrics. Technical Decision-Making & Stakeholder Alignment Document architectural designs, research findings, and Architectural Decision Records (ADRs). Drive consensus with the CTO, local product teams, and global engineering leaders. Highlights of the Role Fundamentally Elevate AI Product Precision: Drive the foundational quality of the data architecture that directly controls the accuracy limits of autonomous AI research agents and matching engines. Direct Business Impact: Quality improvements in company entity resolution and career history directly drive core matching rates (revenue) while minimizing critical compliance risks. End-to-End Ownership from Investigation to CTO Decision-Making: Work directly with complex, real-world legacy and multi-cloud data setups. You will own the full lifecycle—from data investigation and architecture design to CTO alignment and implementation. Navigate Complex Post-Acquisition Environments: Gain rare experience solving large-scale data engineering problems arising from combining distinct tech stacks, data models, and cross-border operations following our 2021 global acquisition of Coleman. Tech Stack ENS Development Common Stack Programming Languages: C#, Python, TypeScript Backend Frameworks: ASP.NET Core, FastAPI Frontend Framework: Angular Infrastructure: Microsoft Azure, Google Cloud Platform Databases: SQL Server, Cosmos DB Communication: Slack, Google Meet, Jira Documentation: esa, Confluence AI Tools: Claude Code, Devin, ChatGPT Data Platform Engineer Specific Tools Azure Data Factory, Microsoft Power BI, BigQuery Requirements Data Engineering & DWH Experience: Proven track record of designing, building, and operating production-grade data pipelines and data warehouse architecture. Relational Database Expertise: Deep hands-on experience with SQL execution plan analysis, index optimization, and high-volume batch processing. Root-Cause Data Investigation: Experience cross-analyzing code logic and raw data to resolve data inconsistencies, pipeline outages, and performance bottlenecks. Technical Documentation & Consensus Building: Strong ability to document architectural choices (design docs, research reports, ADRs) and align technical direction with stakeholders. Backend Development: Hands-on experience developing backend applications in modern programming languages. Language Proficiency: Native or bilingual level Japanese proficiency (essential for analyzing complex local data schemas and collaborating with Japanese domain teams). Nice to Have AI/Search Data Pipelines: Experience providing data foundations for AI/LLM products, RAG systems, or enterprise search platforms. Master Data Management (MDM): Experience with record linkage, entity resolution, deduplication algorithms, and continuous data governance. Distributed System Data Syncing: Debugging and development experience in hybrid environments with event-driven and batch-oriented data syncs. Cloud & Data Stack: Hands-on experience with SQL Server, Azure (AKS, Data Factory), or GCP (BigQuery, Cloud SQL). High-Precision Domains: Engineering experience in domains requiring extreme data precision (e.g., finance, healthcare, authentication, compliance). Master Data Migration: Experience leading multi-source database consolidation, unified schema design, ID mapping, and zero-downtime strangler-pattern migrations. Our Values Sharpen our Edge Excel through Swift Action Place Your Pride Aside Our Success Starts with Me Collaborate without Boundaries Employment Details Employment type: Full-time (permanent employee) Probation period: 3 months after joining (same conditions as after the probation period) Salary: JPY 7,000,000 to JPY 12,000,000 per year (determined based on skills and experience) Monthly pay: JPY 517,000 to JPY 893,000 Base salary: JPY 373,000 to JPY 681,000 Fixed overtime allowance: JPY 123,000 to JPY 252,000 Standard time management: includes 45 hours of fixed overtime and 20 hours of fixed late-night work allowance Discretionary work system (specialized work): includes 30 hours of fixed overtime and 40 hours of fixed late-night work allowance Overtime or late-night work exceeding the fixed allowance is paid in full separately Whether you are placed under the standard time management or the discretionary work system is determined based on your skills, experience, and job responsibilities Salary review: determined based on skills, experience, and ability (reviewed twice a year) Bonus: once a year (based on performance) Location: Sumitomo Fudosan Aobadai Hills 1F/9F, 4-7-7 Aobadai, Meguro-ku, Tokyo Immediately after hiring: Tokyo headquarters and the employee's home Scope of change: the headquarters, locations designated by the company such as group companies, and the employee's home Working hours: standard time management or the discretionary work system for specialized work (determined based on skills, experience, responsibilities, and revisions to internal systems) Standard time management: 10:00 to 19:00 (prescribed working hours: 8 hours 00 minutes / break: 60 minutes) Discretionary work system: deemed working hours of 8 hours per day / break: 1 hour. Average working hours: 160 hours per month (average of development organization members, second half of 2022) Holidays and leave: 127 days off per year Two days off every week (Saturdays, Sundays, and national holidays) Year-end and New Year holidays Annual paid leave (granted from 3 months after joining) Self-development leave (up to 5 consecutive days once a year, separate from annual paid leave) Maternity and parental leave (with a track record of use) Insurance: health insurance, employees' pension insurance, employment insurance, and workers' accident compensation insurance Benefits Commuting allowance (with an upper limit) Performance benefit of up to JPY 10,000 per month (body maintenance, housekeeping services, learning expenses, etc.) Subsidy for attending external seminars Coverage of book purchase costs Influenza vaccinations Coverage of health checkup costs and subsidy for optional health checkup costs Benefits through health insurance (use of resort and sports facilities, restaurant discounts, etc.) Company-leased housing program Relocation cost subsidy for hires moving from distant areas (at the time of hiring only) Subsidy for study sessions and internal social events Subsidy for internal club activities Lunch subsidy for welcoming new employees and internal networking Work style Side jobs: allowed (prior approval required) Remote work: allowed (in the office at least once a week). The office and remote work frequency may change in the future due to changes in company policy. Dress code: free Office: free-address seating, monitors and standing desks, free coffee and snacks, in-house library, space for study sessions, and social gatherings allowed in the office Smoking: no smoking indoors (no smoking room); smoking is prohibited on the entire premises Scope of duties: immediately after hiring, as described in this job description; scope of change, all duties of the company Selection Process Screening / Casual Interview 1st Interview 2nd Interview Final Interview A reference check may be conducted during the selection process. Details, including the timing, will be shared with you during the process.