- Страна
- США
- Зарплата
- 190 000 $ – 212 000 $
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Staff Data Engineer
Высокая оценка обусловлена прозрачным диапазоном зарплаты, удаленным форматом работы и возможностью влиять на архитектуру крупной международной платформы. Компания прибыльна и работает в стабильном секторе e-commerce.
Сложность вакансии
Роль уровня Staff требует не только глубоких технических знаний Snowflake и Kafka, но и навыков архитектурного проектирования и лидерства. Ожидается опыт работы с огромными объемами транзакционных данных и умение выстраивать стратегию развития платформы.
Анализ зарплаты
Предлагаемая зарплата ($190k - $212k) находится на верхнем уровне рыночных ожиданий для Staff Data Engineer в США, особенно для полностью удаленной позиции. Это конкурентное предложение, соответствующее высокой ответственности роли.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Data Engineer position at FastSpring. With over five years of experience in high-growth SaaS environments and a deep specialization in building real-time data architectures, I am confident in my ability to lead the design and implementation of your next-generation data platform. My background in architecting Snowflake ecosystems and managing high-throughput streaming with Apache Kafka aligns perfectly with FastSpring's mission to provide actionable insights from hundreds of millions of rows of transactional data.
In my previous roles, I have successfully implemented CDC pipelines using Debezium and managed complex transformations with dbt and Spark Streaming. I am particularly drawn to this role because it combines technical leadership with the challenge of bridging the gap between complex transactional systems and customer-facing analytics. I am eager to bring my expertise in data APIs and real-time ingestion to help FastSpring continue its innovation in the global ecommerce space.
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Откликнитесь в fastspring уже сейчас
Станьте техническим лидером в FastSpring и проектируйте платформу данных нового поколения для миллионов транзакций!
Описание вакансии
About the Company:
FastSpring is the world’s leading ecommerce platform for SaaS/Software, gaming, and digital product companies. Our product hosts over 10 million transactions per year, powering sales growth for more than 3,500 companies in over 200 countries, using every major currency. We pride ourselves on being an innovative company with an entrepreneurial culture, growth mindset, global influence, and profitable operations.
We are committed to building an inclusive work environment, and we invest in our employees by helping team members grow and develop professionally. We are developers, technologists, and business professionals who are globally-minded, customer-focused, and driven by constant innovation.
Founded in 2005, FastSpring is a privately owned company headquartered in Santa Barbara with offices in Amsterdam, Austin, Belfast and Halifax.
The Position:
FastSpring is looking for a Staff Data Engineer to serve as the technical architect and driving force behind our next-generation data platform. As a key partner to the Senior Data Product Manager, you will build the high-performance infrastructure required to turn hundreds of millions of rows of transactional data into actionable insights for our sellers.
This role is a high-impact technical leadership position responsible for designing and executing a modern data warehouse strategy that supports real-time product innovation. You will bridge the gap between complex transactional systems and the analytical needs of our global customers.
This role reports to the Senior Director, Development, and works cross-functionally with Product, Engineering, and Executive leadership to identify growth opportunities and execute technical go-to-market strategies.
Responsibilities:
- Architect and Implement: Lead the design and construction of a next-generation data warehouse optimized for improved efficiency, performance, and massive scale.
- Real-Time Data Ingestion: Build and maintain robust data pipelines for real-time ingestion from large-scale production transactional databases containing hundreds of millions of rows.
- Stream Processing: Develop real-time data transformation layers to ensure the data warehouse reflects live business activity, enabling "up-to-the-minute" analytics for our ecosystem.
- Technical Roadmap: Partner with the Senior Data Product Manager to define, evangelize, and execute a data roadmap that meets both internal and external customer needs.
- Technical Leadership: Research and select appropriate technical solutions, coordinate delivery with dedicated agile teams, and champion engineering best practices.
- Validation & Metrics: Rigorously test and validate data integrity, establishing and measuring success metrics for system performance and data reliability.
- Collaboration: Work closely with stakeholders to develop technical business cases for new initiatives, ensuring alignment across the development organization.
Qualifications:
- Experience: 5+ years of data engineering experience in a high-growth SaaS environment.
- Real-Time Messaging: Expert-level experience with message brokers and streaming platforms such as Apache Kafka, Amazon Kinesis, or Google Pub/Sub to manage high-throughput transactional data.
- Data Transformation: Proficiency with real-time and batch transformation tools, specifically dbt (data build tool) for managing Snowflake logic and Apache Flink or Spark Streaming for in-flight processing.
- Snowflake Ecosystem: Deep architectural knowledge of Snowflake, including experience with Snowpipe for continuous ingestion, streams, and tasks for change data capture (CDC).
- Database Internals: Strong understanding of schemas and data pipelines, with specific experience extracting data from large-scale relational databases (Postgres/MySQL) via CDC tools like Debezium.
- Technical Proficiency: Mastery of SQL and Python for building automated, scalable data movement and transformation workflows.
- Data APIs: Proven experience designing and maintaining Data APIs to expose warehouse insights to external or internal customers.
- Business Intelligence: Familiarity with business intelligence tools such as Looker.
- Communication: Exceptional ability to synthesize complex technical concepts and communicate them clearly to stakeholders, including the Senior Data Product Manager and executive leadership.
Payments Domain: (Preferred) Experience with the data structures associated with payment processors, gateways, and card networks.
Consistent with FastSpring's values and applicable law, we provide the following information to promote pay transparency and equity. The base pay range below represents a good faith estimate of the low and high end base pay range for the listed position. This role may be eligible for the corporate bonus plan (or, if a sales role, a commission plan as defined in the sales incentive plan document). In addition, FastSpring provides a variety of benefits to employees.
Estimated Base Pay Range
$190,000—$212,000 USD
About the Company:
FastSpring is an EQUAL EMPLOYMENT OPPORTUNITY/AFFIRMATIVE ACTION employer. Candidates are considered for employment with FastSpring without regard to their race, color, religion, national origin, age, sex, gender, pregnancy, disability, sexual orientation, gender identity, genetic information, military status, veteran status (specifically status as a disabled veteran, special disabled veteran, Vietnam Era veteran, recently separated veteran, armed forces service medal veteran, or other protected veteran) or other classification protected by applicable federal, state or local law.
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Навыки
- Python
- SQL
- Looker
- dbt
- PostgreSQL
- Snowflake
- Apache Flink
- MySQL
- Apache Kafka
- Change Data Capture
- Debezium
- Amazon Kinesis
- Google Pub/Sub
- Apache Spark Streaming
- Data API
Возможные вопросы на собеседовании
Проверка опыта работы с ключевым стеком компании и понимания архитектуры Snowflake.
Опишите ваш опыт настройки Snowpipe и потоков (streams) в Snowflake для обеспечения непрерывной инкубации данных. С какими основными проблемами производительности вы сталкивались?
Вакансия требует навыков работы с CDC для извлечения данных из транзакционных БД.
Как бы вы спроектировали отказоустойчивый конвейер CDC с использованием Debezium и Kafka для базы данных Postgres объемом в сотни миллионов строк?
Роль подразумевает выбор технологий и обоснование решений.
В каких случаях вы бы предпочли Apache Flink вместо Spark Streaming для обработки данных 'в полете' (in-flight processing) в контексте FastSpring?
Staff-позиция требует взаимодействия с бизнесом.
Как вы подходите к приоритизации технического долга в архитектуре данных по сравнению с запросами на новые фичи от продуктовых менеджеров?
Проверка навыков обеспечения качества данных.
Какие метрики и инструменты вы считаете критически важными для мониторинга целостности и актуальности данных в реальном времени?
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- Страна
- США
- Зарплата
- 190 000 $ – 212 000 $