{"id":63201,"url":"https://alion.io/job/estie-backend-engineer-data","title":"Backend Engineer (Data)","company":{"id":20874,"name":"estie","domain":"estie.jp","url":"https://alion.io/company/estie","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HRMOS","truth_index":{"grade":"D","score":46,"open_postings":19,"ghost_share":0.895,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tokyo, Japan"],"countries":["JP"],"hiring_countries":["JP"],"hiring_countries_total":1,"salary":{"min":6000000,"max":10000000,"currency":"JPY","period":"year","gross":null,"usd_annual":62850},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-08-19T02:01:43Z","employer_posted_date":null,"last_verified_at":"2026-08-19T02:01:43Z","board_verified":false,"closed_at":null,"days_open":59,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":59},"description":"Background of the Position\nestie is building a real estate database through the power of data and technology. By leveraging data, we aim to uncover the hidden value of cities, enabling them to realize their full potential and enriching the lives of the people who live there.\nCommercial real estate includes properties such as offices, station buildings, and shopping centers. Although Tokyo is the world’s largest commercial real estate market, it is not widely known that much of its data remains fragmented and buried, creating a barrier to better urban development.\nWe have launched “estie Market Research,” an urban data analytics platform, and the products we have released since then have also been well received by our clients. However, we are still far from where we aspire to be. To realize a future in which Japanese cities can compete on the global stage, we need more people and greater capabilities.\nFor this reason, the Data Management Group is looking for new members to help us solve these challenges.\nAbout the Team\nThe Data Management Group is responsible for creating and continuously improving the real estate data provided through estie’s products, using the power of software.\nReal estate information exists in fragmented forms and often contains inconsistent naming and missing values, making it difficult to use directly for analysis and decision-making. Our team transforms this complex information into data models capable of handling historical changes, and designs and develops automated pipelines and APIs for data collection, normalization, entity resolution, and distribution, as well as internal systems that continuously improve data quality.\nEngineers and data operators work together, combining automated processing with human judgment to create highly reliable data products that do not yet exist in the industry. We also communicate directly with business teams and customers, taking end-to-end responsibility from defining the required data to implementing and delivering it through our products.\nRather than simply supporting our data infrastructure, we are a team that expands the possibilities of estie’s business and the real estate industry through the data itself.\nSpecific Responsibilities\nAs a software engineer, you will build data pipelines that generate the real estate data provided to users. Your responsibilities will include:\nBuilding systems for collecting real estate information, including data entry systems, integration APIs, and batch processing systems\nModeling collected real estate data so that it can be integrated into a shared data platform\nImplementing and operating data processing infrastructure and pipelines that perform ETL, normalization, and entity resolution on collected real estate data, making it available as time-series data (Python, dbt, Terraform)\nImplementing and operating backend API servers required by the above data processing pipelines, including geocoding, machine learning, and data distribution APIs (Python, Rust)\nBuilding and operating internal systems for correcting and maintaining data (Rust, React, Python)\nBuilding and operating data pipelines and BI dashboards that visualize management metrics such as revenue, as well as product usage data, for executives and business teams\nBuilding and operating AI-ready data infrastructure using technologies such as Snowflake Cortex AI\nWhat Makes This Position Exciting / What You Will Gain\nThe intellectual challenge of translating complex real-world real estate information into structured data representations\nExperience creating high-quality data as a product and directly contributing to business value\nExperience supporting customers’ operations by expanding the range of data offered and improving its quality\nExperience contributing to long-term value creation through technical proposals for complex processing requirements arising from business needs\nOpportunities to grow by solving difficult problems alongside highly skilled engineers, including OSS committers and top-ranked competitive programmers\nExperience developing internal data infrastructure and leveraging data to support a highly uncertain, unprecedented business in a data-driven manner\nRequired Skills\nFundamental understanding of computer science, including data structures and computational complexity\nAt least approximately two years of experience developing and operating web backend systems or server-side processing systems such as batch processing\nDevelopment experience using relational databases such as MySQL or PostgreSQL\nExperience with team-based software development using version control systems such as Git and ticket/issue management systems\nPreferred Skills\nExperience developing backend systems using statically typed languages such as Rust, Go, or Kotlin\nExperience using data warehouse products such as Snowflake, BigQuery, Databricks, or Redshift\nExperience developing deep expertise in a specific domain and designing or modeling its business logic\nInterest in Rust\nKnowledge of machine learning\nDevelopment experience using BI tools such as Tableau or Looker\nWho We Are Looking For\nSomeone who enjoys providing data as a product and is passionate about continuously pursuing higher data quality\nSomeone who finds satisfaction in breaking down difficult business 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