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SeniorГибридПолная занятость

Software Engineer, Data Engineering

Оценка ИИ

Отличная вакансия в известной компании с сильной инженерной культурой и очень конкурентной заработной платой. Работа над сложными задачами мирового масштаба и щедрый пакет льгот делают это предложение крайне привлекательным для опытных инженеров.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена требованием к опыту (от 10 лет), необходимостью глубоких знаний в распределенных системах и опытом работы с экстремальными нагрузками (миллиарды событий в день). Роль подразумевает не только разработку, но и архитектурное лидерство вместе с менторством.

Анализ зарплаты

Медиана210 000 $
Рынок185 000 $ – 280 000 $
Оценка ИИ

Предлагаемый диапазон $200,000 – $265,000 полностью соответствует и даже несколько превышает средние рыночные показатели для Senior Data Engineer в Сан-Франциско, где медиана составляет около $210,000. Верхняя граница в $265k является очень сильным предложением для индивидуального контрибьютора.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Software Engineer, Data Engineering position at Superhuman. With over a decade of experience in building large-scale distributed systems and a proven track record of managing high-load production environments, I am excited by the challenge of scaling a platform that processes over 60 billion daily events. My expertise in Spark, Kafka, and Terraform, combined with a strategic approach to data modeling, aligns perfectly with your mission to unlock superhuman potential through AI-driven productivity.

Throughout my career, I have focused on architecting robust ETL/ELT pipelines and implementing scalable data lake solutions using technologies like Delta Lake and Snowflake. I am particularly drawn to Superhuman’s culture of innovation and the opportunity to mentor engineers while shaping the technical roadmap of the Data Platform team. I am confident that my background in designing secure, high-uptime systems will contribute significantly to your team's success in San Francisco.

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Присоединяйтесь к команде Superhuman и создавайте платформу данных мирового уровня, обрабатывающую 70 миллиардов событий ежедневно!

Описание вакансии

Superhuman offers a dynamic hybrid working model for this role. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.

Superhuman team members in this role must be based in San Francisco or Seattle.

About Superhuman

Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company’s products include Grammarly’s writing assistance, Coda’s collaborative workspaces, Mail’s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically. Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at superhuman.com and about our values here.

The Opportunity

To achieve our ambitious goals, we’re looking for a Senior Engineer to join our Data Platform team and help us build a world-class data platform. Superhuman success depends on its ability to efficiently ingest over 60 to 70 billion daily events while using our systems to improve our product. This role presents a unique opportunity to experience all aspects of building complex software systems, including contributing to the strategy, defining the architecture, and developing and shipping to production.

Superhuman's engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.

Overview

As a Software Engineer on the Data Platform team, you will shape the architecture and technical strategy of our data platform, ensuring scalability, security, and efficiency across data engineering systems. You will design and lead the implementation of robust, scalable, and reliable systems that handle large volumes of data, empowering both product features and data-driven decision-making across the company. Your work will span areas such as real-time & ETL data pipelines, cloud infrastructure, data lakes, and back-end services.

This role requires you to collaborate with cross-functional teams, including back-end engineers, Analytics engineering, Data Science engineering, and machine learning teams, to drive initiatives that support various business outcomes. As a senior IC, you will also mentor engineers and help set the strategic direction for the platform.

In this role, you will:

  • Architect and lead the development of large-scale systems for data pipelines, data lakes that handle billions of daily events.
  • Design and implement solutions that ensure data is available, secure, and scalable across the platform, enabling real-time and batch processing.
  • Make high-level architectural decisions about system design, technology choices, and platform evolution, ensuring scalability and long-term sustainability.
  • Collaborate with key stakeholders, such as product teams, data engineers, back-end developers, and ML engineers, to build tools & frameworks that power analytics, product features, and data-driven workflows.
  • Work with business stakeholders such as Analytics Engineering and Data Science teams to build high-impact data products enabling business-critical features, research, and experimentation with a focus on efficiency and alignment
  • Collaborate with Leadership in devising the charter and technical roadmaps
  • Mentor engineers across back-end infrastructure and data engineering disciplines, fostering a culture of collaboration and technical excellence.

Qualifications

  • Brings at least 10 years of experience in large-scale distributed computing systems, with expertise in both data engineering and data modeling.
  • Has 5+ years of experience managing live production environments, including high-load systems or data-intensive workflows with a focus on uptime and reliability.
  • Expert in SQL and proficient in technologies like Spark, Kafka, Terraform, and in at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java).
  • Strong knowledge of ETL/ELT design patterns, orchestration tools (e.g., Airflow, dbt, Dagster), and data quality frameworks.
  • Ability to design scalable, secure, and maintainable data models and architectures, and understanding of data governance, privacy regulations (GDPR/CCPA).
  • Hands-on experience with modern data storage technologies (e.g., Delta Lake, Snowflake, BigQuery, Redshift).
  • Is a strategic thinker, able to evaluate whether to build internally or leverage third-party solutions, ensuring the right balance between speed, scalability, and long-term viability.
  • Is an excellent communicator and collaborator, able to work across diverse teams and stakeholders, translates business needs into robust data solutions, and ensures alignment on technical goals.
  • Has a demonstrated ability to work independently with minimal guidance, proactively manages tasks and priorities across multiple projects, analyzes and executes work efficiently, collaborates effectively with cross-functional teams, and thrives in fast-paced, results-driven environments

Compensation and Benefits

Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more:

  • Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits)
  • Disability and life insurance options
  • 401(k) and RRSP matching
  • Paid parental leave
  • 20 days of paid time off per year, 12 days of paid holidays per year, two floating holidays per year, and flexible sick time
  • Generous stipends (including those for caregiving, pet care, wellness, your home office, and more)
  • Annual professional development budget and opportunities

Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Our US locations are categorized into two compensation zones based on proximity to our hub locations. Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by compensation zone and may be modified in the future.

Zone 1: $200,000 to $265,000 (USD)

We encourage you to apply

At Superhuman, we value our differences, and we encourage all to apply—especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada).

#LI-Hybrid

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Spark
  • Kafka
  • Terraform
  • SQL
  • Python
  • Scala
  • Java
  • Airflow
  • dbt
  • Dagster
  • Delta Lake
  • Snowflake
  • BigQuery
  • Redshift
  • ETL
  • Data Modeling
  • Distributed Systems

Возможные вопросы на собеседовании

Проверка опыта работы с масштабируемыми системами, что критично для 70 млрд событий в день.

Опишите архитектурное решение, которое вы разработали для обработки потоковых данных в масштабе миллиардов событий. С какими узкими местами вы столкнулись?

Вакансия требует навыков в Terraform и облачной инфраструктуре.

Как вы подходите к обеспечению надежности и отказоустойчивости инфраструктуры данных при использовании принципов Infrastructure as Code?

Важно понимать умение кандидата выбирать между готовыми решениями и собственной разработкой.

Расскажите о случае, когда вам пришлось выбирать между внедрением стороннего инструмента (например, Snowflake/Databricks) и созданием собственного решения. Какими критериями вы руководствовались?

Роль Senior подразумевает работу с качеством и управлением данными.

Как вы организуете мониторинг качества данных и соблюдение требований GDPR/CCPA в сложных распределенных пайплайнах?

Проверка лидерских качеств и умения развивать команду.

Опишите ваш подход к менторству инженеров. Как вы помогаете команде поддерживать высокий уровень технического совершенства?

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