▍Why We Are Hiring The era when revenue grew with headcount is over. We aim to grow ARR per employee tenfold in three years from November 2025. On the data side, that means redesigning how corporate data is collected, matched, and verified. You set the collection requirements and quality criteria behind SalesNow MCP and the Data API: which sources to trust, what evidence a record needs, and when a result is good enough to ship. ▍Mission Build structured company profiles that capture what each company does and what changed recently. You define the matching rules that tell apart companies with the same name and absorb address changes, mergers, and relocations. ▍What You Will Do Our data platform runs at tens of terabytes. You will work on: ・Pipelines for web data crawling ・Data cleansing and enrichment ・A monitoring environment for data quality ・Scalability, performance, and cost efficiency ・Data quality foundations for future data science use ※Scope of changes to duties: yes（従事すべき業務の変更の範囲：有り） ▍Requirements ・Currently living in Japan, or able to relocate to Japan ・Business-level Japanese communication skills (JLPT N1 or equivalent) ・Experience processing data with SQL and Python ・Experience with public cloud platforms ▍Nice to Have ・Apache Spark (including PySpark) / AWS analytics services / Databricks ・Data management experience / Alignment with DataOps principles ▍Why Join 【1】8 billion records from three routes, including offline collection and user contributions no crawler reaches. You design the entity matching behind the screen and SalesNow MCP. 【2】You decide what to collect and when a record is fit to ship. When the routes disagree, you set which evidence wins. 【3】Production workflows run LLMs on real company data; you decide what a person verifies before a result ships. 【4】Our executives write code themselves. Fully remote, full flex. ▍Hiring Process Application screening → Interviews (multiple rounds) → Reference check → Offer meeting (offer)