- Страна
- США
- Зарплата
- 168 000 $ – 240 000 $
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Staff Data Engineer
Отличная вакансия в топовой криптокомпании с прозрачным диапазоном зарплаты и сильным соцпакетом. Высокий балл за возможность влиять на архитектуру глобального продукта и работу с передовым стеком технологий.
Сложность вакансии
Роль уровня Staff требует не только глубоких технических знаний (Python, Spark, Streaming), но и развитых лидерских качеств для менторства и проектирования архитектуры. Высокая планка обусловлена спецификой криптоиндустрии и необходимостью работы с высоконагруженными системами в реальном времени.
Анализ зарплаты
Предложенная зарплата ($168k - $240k) полностью соответствует рыночным стандартам для Staff-позиций в Нью-Йорке и Сан-Франциско. Верхняя граница диапазона даже несколько превышает медиану, что делает предложение очень конкурентоспособным, учитывая дополнительные бонусы и опционы.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Data Engineer position at Gemini. With over 8 years of experience in building large-scale data systems and a deep expertise in Python, SQL, and Spark, I have consistently delivered robust ETL/ELT pipelines that power critical business insights. My background in designing real-time streaming solutions using Kafka and Flink aligns perfectly with Gemini's mission to provide secure and reliable access to the cryptoeconomy.
In my previous roles, I have successfully led architectural initiatives and mentored engineering teams to adopt best practices in data modeling and observability. I am particularly drawn to Gemini's commitment to bridging traditional finance with Web3, and I am eager to apply my experience with Databricks and AWS to optimize your data infrastructure. I am confident that my technical leadership and passion for the crypto space will contribute significantly to the Data Team's success.
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Описание вакансии
About the Company
Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure. As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.
The Department: Data
At Gemini, our Data Team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.
The Role: Staff Data Engineer
The Data team is responsible for designing and operating the data infrastructure that powers insight, reporting, analytics, and machine learning across the business. As a Staff Data Engineer, you will lead architectural initiatives, mentor others, and build high-scale systems that impact the entire organization. You will partner closely with product, analytics, ML, finance, operations, and engineering teams to move, transform, and model data reliably, with observability, resilience, and agility.
This role is required to be in person twice a week at either our San Francisco, CA or New York City, NY office.
Responsibilities:
- Lead the architecture, design, and implementation of data infrastructure and pipelines, spanning both batch and real-time / streaming workloads
- Build and maintain scalable, efficient, and reliable ETL/ELT pipelines using languages and frameworks such as Python, SQL, Spark, Flink, Beam, or equivalents
- Work on real-time or near-real-time data solutions (e.g. CDC, streaming, micro-batch) for use cases that require timely data
- Partner with data scientists, ML engineers, analysts, and product teams to understand data requirements, define SLAs, and deliver coherent data products that others can self-serve
- Establish data quality, validation, observability, and monitoring frameworks (data auditing, alerting, anomaly detection, data lineage)
- Investigate and resolve complex production issues: root cause analysis, performance bottlenecks, data integrity, fault tolerance
- Mentor and guide more junior and mid-level data engineers: lead code reviews, design reviews, and best-practice evangelism
- Stay up to date on new tools, technologies, and patterns in the data and cloud space, bringing proposals and proof-of-concepts when appropriate
- Document data flows, data dictionaries, architecture patterns, and operational runbooks
Minimum Qualifications:
- 8+ years of experience in data engineering (or similar) roles
- Strong experience in ETL/ELT pipeline design, implementation, and optimization
- Deep expertise in Python and SQL writing production-quality, maintainable, testable code
- Experience with large-scale data warehouses (e.g. Databricks, BigQuery, Snowflake)
- Solid grounding in software engineering fundamentals, data structures, and systems thinking
- Hands-on experience in data modeling (dimensional modeling, normalization, schema design)
- Experience building systems with real-time or streaming data (e.g. Kafka, Kinesis, Flink, Spark Streaming), and familiarity with CDC frameworks
- Experience with orchestration / workflow frameworks (e.g. Airflow)
- Familiarity with data governance, lineage, metadata, cataloging, and data quality practices
- Strong cross-functional communication skills; ability to translate between technical and non-technical stakeholders
- Proven experience in mentoring, leading design discussions, and influencing data-engineering best practices across teams
Preferred Qualifications:
- Experience with crypto, financial services, trading, markets, or exchange systems
- Experience with blockchain, crypto, Web3 data — e.g. blocks, transactions, contract calls, token transfers, UTXO/account models, on-chain indexing, chain APIs, etc.
- Experience with infrastructure as code, containerization, and CI/CD pipelines
- Hands-on experience managing and optimizing Databricks on AWS
It Pays to Work Here
The compensation & benefits package for this role includes:
- Competitive starting pay
- A discretionary annual bonus
- Long-term incentive in the form of a new hire equity grant
- Comprehensive health plans
- 401K with company matching
- Paid Parental Leave
- Flexible time off
Salary Range: The base salary range for this role is between $168,000 - $240,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.
In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in-person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce.
At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.
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Навыки
- Python
- SQL
- Spark
- Flink
- Apache Beam
- Databricks
- BigQuery
- Snowflake
- Kafka
- Amazon Kinesis
- Airflow
- AWS
- ETL
- ELT
- CDC
- Data Modeling
Возможные вопросы на собеседовании
Для уровня Staff критически важно умение проектировать отказоустойчивые системы.
Опишите архитектуру стриминговой системы с использованием CDC, которую вы проектировали. Как вы обеспечивали гарантии доставки сообщений (exactly-once) и обрабатывали сбои?
Проверка навыков оптимизации затрат и производительности в облаке.
Какие стратегии оптимизации производительности и стоимости вы применяли при работе с Databricks на больших объемах данных?
Оценка лидерских качеств и умения влиять на процессы.
Расскажите о случае, когда вам пришлось убеждать кросс-функциональную команду принять сложное архитектурное решение. Как вы аргументировали свою позицию?
Проверка понимания специфики данных в криптосфере.
С какими специфическими проблемами качества данных вы сталкивались при индексации блокчейн-транзакций или работе с рыночными данными?
Оценка навыков менторства.
Как вы подходите к проведению код-ревью и архитектурных ревью для мидл-разработчиков, чтобы способствовать их профессиональному росту?
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- Страна
- США
- Зарплата
- 168 000 $ – 240 000 $