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whatnot
Страна
США
Зарплата
195 000 $ – 230 000 $
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Data Engineer, Notifications

Оценка ИИ

Отличная вакансия в одном из самых быстрорастущих стартапов США с прозрачной и высокой зарплатой. Предлагается сильный пакет бенефитов, работа с передовыми технологиями и реальное влияние на продукт, которым пользуются миллионы.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью работы с огромными объемами данных (сотни миллионов событий в день) и требованием глубокой экспертизы в современном стеке (Snowflake, dbt, Kafka). Роль предполагает полную ответственность за архитектуру домена и тесное взаимодействие с ML-командами.

Анализ зарплаты

Медиана190 000 $
Рынок165 000 $ – 225 000 $
Оценка ИИ

Предлагаемая зарплата ($195k - $230k) находится на верхней границе рыночного диапазона для Senior Data Engineer в Сан-Франциско. Это подчеркивает высокую значимость роли и готовность компании платить за топовую экспертизу.

Сопроводительное письмо

I am writing to express my interest in the Data Engineer position for the Notifications Platform at Whatnot. With over 5 years of experience in building production-grade data pipelines and managing large-scale datasets, I am excited by the opportunity to own the end-to-end data architecture for one of your most high-impact domains. My background in optimizing Snowflake workloads and implementing robust dbt models aligns perfectly with your need for a scalable, reliable data mart.

In my previous roles, I have successfully navigated the complexities of high-volume event processing and cross-functional collaboration between ML and Product teams. I am particularly drawn to Whatnot’s fast-paced environment and the challenge of setting new patterns for domain-owned data engineering. I am eager to bring my expertise in SQL, Python, and modern orchestration tools like Dagster to help Whatnot continue its impressive growth as the leader in livestream shopping.

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Составьте идеальное письмо к вакансии с ИИ-агентом

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Откликнитесь в whatnot уже сейчас

Присоединяйтесь к Whatnot и создавайте будущее лайв-коммерции, управляя данными в масштабе сотен миллионов событий!

Описание вакансии

🚀 Join the Future of Commerce with Whatnot!

Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.

As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.

We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.

💻 Role

At Whatnot data engineers build foundational data systems that power product development, experimentation, machine learning, and operational decision-making across the company. As an Data Engineer on the Notifications Platform, you will play a critical role in owning and evolving one of the highest-volume and highest-impact data domains at Whatnot.

Notifications generate hundreds of millions of events per day, and the underlying data systems support everything from ML iteration and experimentation to adhoc engineering debugging. In this role, you will define the technical direction for the Notifications data mart, harden it to production-grade reliability, and set new patterns for domain-owned data engineering.

Working in a highly cross-functional role, you will collaborate closely with Product Engineers, Data Scientists, ML Engineers, and the Analytics Platform team. You’ll make key architectural decisions around data modeling, reliability, latency, and cost — and then make them real.

On any given day, you will:

  • Own data architecture end-to-end. Define how we capture, model, and serve critical business data—then implement it in production. You’ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
  • Build mission-critical pipelines. Develop and operate batch data workflows that process high-volume events related to notifications with tight guarantees for latency, completeness, and accuracy.
  • Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and production applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
  • Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
  • Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
  • Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, self-healing, maintainable data assets.

We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.

👋 You

Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.

As our next Data Engineer, you bring deep experience designing reliable, scalable data systems and are excited to take true ownership of a complex product domain.

You should have 5+ years of experience in the data or software engineering domain, plus:

  • Strong experience building and maintaining production-grade data pipelines with clear SLAs, monitoring, and alerting
  • Deep expertise in SQL, including complex model graphs, dependency management, and performance optimization
  • Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
  • Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
  • Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
  • Proven track record working with large-scale datasets (hundreds of millions of rows per day)
  • Experience designing data models that balance analytics, ML, and operational debugging use cases
  • Strong systems thinking — you consider correctness, latency, cost, and maintainability together
  • Self-starter ethic, thriving under a high level of autonomy
  • Exceptional interpersonal and communication skills in cross-functional environments

💰Compensation For Full-Time (Salary)

US based applicants: $195,000/year to $230,000/year + benefits + equity.

The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.

🎁 Benefits

  • Generous Holiday and Time off Policy
  • Health Insurance options including Medical, Dental, Vision
  • Work From Home Support

+ Home office setup allowance

+ Monthly allowance for cell phone and internet

  • Care benefits

+ Monthly allowance for wellness

+ Annual allowance towards Childcare

+ Lifetime benefit for family planning, such as adoption or fertility expenses

  • Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
  • Monthly allowance to dogfood the app

+ All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).

  • Parental Leave

+ 16 weeks of paid parental leave + one month gradual return to work \*company leave allowances run concurrently with country leave requirements which take precedence.

1212

💛 EOE

Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Python
  • SQL
  • dbt
  • CI/CD
  • BigQuery
  • Infrastructure as Code
  • Snowflake
  • Airflow
  • Kafka
  • Spark
  • Flink
  • Dagster
  • Great Expectations
  • Redshift
  • Debezium
  • Monte Carlo

Возможные вопросы на собеседовании

Учитывая объем в сотни миллионов событий, важно понимать, как кандидат обеспечивает надежность и соблюдение SLA.

Как бы вы спроектировали систему мониторинга и алертинга для пайплайна уведомлений, чтобы гарантировать точность и своевременность данных?

Вакансия требует опыта работы с облачными хранилищами и оптимизации затрат.

Опишите ваш опыт оптимизации производительности и стоимости запросов в Snowflake или BigQuery при работе с терабайтными наборами данных.

Роль подразумевает создание канонических моделей для разных потребителей (ML, аналитика).

Как вы подходите к проектированию схем данных, которые должны одновременно поддерживать и оперативную отладку, и обучение моделей машинного обучения?

Whatnot использует современный стек (dbt, Dagster/Airflow).

Расскажите о самом сложном графе зависимостей, который вы создавали в dbt. Как вы решали проблемы с качеством данных и происхождением (lineage)?

Работа в Whatnot требует высокой автономности и инициативности.

Приведите пример, когда вы самостоятельно определили техническое направление для целого домена данных. С какими трудностями вы столкнулись при внедрении новых стандартов?

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whatnot
Страна
США
Зарплата
195 000 $ – 230 000 $