обновлено 8 дней назад
Product Engineer, Backend (Product Data) (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Product Engineer, Backend (Product Data) (AI) (catalog data and enrichment): Building and operating product catalog schemas, partner-data ingestion pipelines, and enrichment services for Mercari Marketplace with an accent on metadata modeling, identifier mapping, and data quality. Focus on designing stable downstream contracts, monitoring correctness and freshness across large datasets, and improving taxonomy, internal tooling, and multilingual catalog readiness.
Location: Hybrid, Minato, Japan; office in Roppongi
Company
operates a marketplace that connects people and circulates physical and digital value through technology.
What you will do
- Design and evolve product catalog schemas, identifier strategies, and documented contracts for downstream teams.
- Build, operate, and improve SQL and service-code pipelines that ingest, normalize, and enrich partner data.
- Maintain category taxonomies, mapping datasets, configurations, and safe fallbacks for unmapped cases.
- Define category-specific attribute requirements and quality rules for facets, filters, and browsing.
- Establish validation, coverage, freshness, monitoring, release, rollback, and operational workflows.
- Improve operator and administrator tools and support multilingual catalog and attribute labels through i18n.
Requirements
- Strong catalog and metadata domain modeling experience across products, SKUs, categories, brands, makers, attributes, and identifier mapping.
- Strong SQL skills and experience building data transformations and enrichment logic.
- Experience operating data pipelines or data-heavy services with validation, monitoring, and incident readiness.
- Ability to document systems clearly and align multiple teams on contracts and rollout plans.
- Backend or service development experience with ownership across design, implementation, on-call, and operations.
- Business-level English or above required; Japanese is welcome but not required.
Nice to have
- Experience operating long-lived external partner data integrations.
- Experience with multilingual data modeling and i18n workflows for catalogs and attributes.
- Experience with event-driven pipeline patterns such as pub/sub fanout, retries, and dead-letter queues.
Culture & Benefits
- Full-time employment with a full flextime schedule and no core time.
- Product Engineers own work end to end, from specification definition through delivery.
- Engineering principles emphasize product focus, collaborative growth, mechanism-based problem solving, and open collaboration.
- Development follows an AI-native approach focused on speed and customer value.
Hiring process
- Application screening followed by an engineering skill assessment through HackerRank or GitHub.
- Interviews may vary by position, followed by an online reference check around the final interview.
- Offer decisions consider the final interview and reference-check results.
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