14 часов назад
Product Engineer (Data Platform)
170 000 - 300 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Product Engineer (Data Platform): Build and own data products and shared systems that power a live map of the working world with an accent on data quality, entity resolution, and scalable data product delivery. Focus on designing data models, integrating LLMs in production, and ensuring reliable, fast, and correct data experiences for thousands of customers.
Location
Location: New York or San Francisco, hybrid work format
Salary
$170K – $300K per year, with equity
Company
is a fast-growing startup with over 11,000 customers and a $5B valuation, focused on helping organizations turn growth ideas into reality using unique data, signals, and AI research.
What you will do
- Decide what the data means by evaluating sources, resolving conflicts, and modeling entities and relationships.
- Explore and build new data products from customer problems through prototyping to product experience.
- Build and maintain the shared data foundation including data ingestion, modeling, versioning, and release evaluation.
- Own data serving systems supporting interactive search, enrichment lookups, and alerts with predictable performance.
- Build and improve models that read the web and validate each other's work to enhance data quality and scalability.
- Make quality a product decision by measuring coverage, correctness, freshness, and source traceability.
Requirements
- Location: Must be based in New York or San Francisco with hybrid work format.
- 8+ years of engineering experience building reliable data products.
- Strong product management skills with ability to lead cross-functional technical work end-to-end.
- Proficiency in Python and SQL, with experience in data modeling, distributed jobs, and failure recovery.
- Experience with entity resolution, graph or temporal data, and integrating LLMs in production.
- Excellent communication skills and collaborative mindset.
Nice to have
- Experience with search infrastructure or data-intensive product systems.
- Experience operating on large third-party datasets.
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