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Staff Data Engineer
Отличная позиция для опытного инженера: высокий уровень влияния, современный стек (AWS, Redshift, Airflow) и возможность работать удаленно в стабильной SaaS-компании. Наличие бонусов и четко прописанных ценностей добавляет привлекательности.
Сложность вакансии
Роль уровня Staff предполагает высокую степень ответственности за архитектуру всей компании, а не только написание кода. Требуется глубокая экспертиза в распределенных системах, управлении данными и лидерские качества для влияния на смежные команды.
Анализ зарплаты
Зарплата в объявлении не указана, но для позиции уровня Staff Data Engineer в США рыночный диапазон составляет $180,000 – $240,000 в год в зависимости от штата и опыта. Это соответствует топовому сегменту рынка для удаленной работы.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Data Engineer position at Foley. With extensive experience in designing enterprise data architectures and building scalable ELT/ETL pipelines using Python, SQL, and Airflow, I am confident in my ability to lead the evolution of your Enterprise Data Model. My background in implementing robust data governance and RBAC, combined with a deep understanding of AWS and Redshift, aligns perfectly with your technical requirements.
Throughout my career, I have demonstrated a commitment to technical leadership and cross-functional collaboration. I thrive on solving complex, ambiguous data problems and turning them into scalable solutions that drive business value. I am particularly excited about Foley's mission to reimagine safety-sensitive industries through an AI-ready platform and would welcome the opportunity to bring my expertise in data modeling and system reliability to your talented team.
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Описание вакансии
We are looking for a Staff Data Engineer to help us design, build, and scale the data systems that power how Foley operates and grows. In this role, you will lead the development of robust data pipelines, shape our enterprise data architecture, and set the standard for how we model, govern, and access data across the organization.
You will operate as a technical leader, influencing how teams think about data, enabling better decisions, and ensuring our systems are scalable, reliable, and built for the future.
What you’ll do
Data Architecture & Strategy
- Lead the design and evolution of our enterprise data architecture, contributing to our Enterprise Data Model (EDM) initiative
- Define standards and best practices for data modeling, storage, and access across systems
- Drive architectural decisions that balance scalability, performance, and maintainability
Pipeline Development & Execution
- Design, build, and maintain scalable data pipelines across internal databases, vendor systems, and our data warehouse
- Ensure high data quality, reliability, and observability across all pipelines
- Optimize data workflows for performance and efficiency
Data Modeling & Governance
- Own data warehouse schema design (e.g., dimensional modeling, normalization strategies)
- Define and implement role-based access control (RBAC) and data governance best practices
- Partner with stakeholders to ensure data definitions are clear, consistent, and trusted
Cross-Functional Leadership
- Act as a technical expert and partner to Engineering, Product, Analytics, and Business teams
- Influence decisions through strong communication, clear tradeoffs, and practical solutions
- Raise the bar for data engineering practices across the organization
Innovation & Continuous Improvement
- Identify opportunities to improve how we work through automation, tooling, and AI
- Experiment thoughtfully with new approaches and scale what works
- Continuously improve system design, development practices, and team effectiveness
Who you are
Must-haves
- Deep expertise in database architecture and distributed data systems
- Strong experience building and maintaining ETL/ELT pipelines in production environments
- Proven ability to design scalable data warehouse schemas and data models
- Experience implementing data governance practices, including RBAC
- Strong software engineering fundamentals (backend systems, data processing, reliability)
- Ability to operate at a Staff level: driving technical direction and influencing across teams
- Experience with Python, SQL, AWS, Redshift, Airflow
Nice-to-haves
- Experience building or supporting machine learning (ML) pipelines in production environments
- Experience partnering with Data Science teams to develop and operationalize data products
You might thrive in this role if you:
- Think in systems and tradeoffs, not just tools or implementations
- Enjoy solving complex, ambiguous data problems and turning them into scalable solutions
- Communicate clearly with both technical and non-technical stakeholders
- Take ownership of outcomes and raise the bar for those around you
- Are curious and proactive about using new tools, including AI, to improve how work gets done
Location: This role is primarily remote (US-based) and operates in EST hours, with occasional travel for team collaboration and company events.
This role may be based remotely out of the following states: Arizona, California, Colorado, Connecticut, Florida, Georgia, Illinois, Indiana, Kansas, Maryland, Massachusetts, Nebraska, New Hampshire, New Jersey, New York, North Carolina, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Virginia, and Wisconsin.
About us
At Foley, we’re reimagining how safety-sensitive industries hire, stay compliant, and manage risk. We’ve evolved into a modern SaaS company with an all-in-one, AI-ready platform that helps transportation, construction, distribution, and utility businesses operate faster, smarter, and safer.
As we continue to grow, we’re looking for curious, strategic thinkers who thrive in complexity, are motivated by making an impact, and want to join a team that’s passionate about building great products and supporting customers. Our core values — Teammateship, Grit, and Innovation — guide everything we do. Whether we’re collaborating internally or helping customers, we approach every challenge with optimism, humor, and a shared commitment to success.
Benefits
Foley offers a comprehensive benefits package that includes medical, dental, and vision coverage, a 401(k) with company match, paid time off and holidays, wellness programs, and an employee assistance program.
Equal Employment Opportunity
Foley is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, protected veteran status, or any other legally protected characteristic.
Reasonable Accommodations
If you require a reasonable accommodation during the application or interview process, please contact us at careers@foley.io
Employment Status
Employment with Foley is on an at-will basis. Nothing in this job posting or in future communications should be construed as a contract of employment.
Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
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Навыки
- AWS
- Data Architecture
- Python
- RBAC
- SQL
- Airflow
- Backend Development
- Distributed Systems
- ETL
- Data Modeling
- Data Governance
- ELT
- Redshift
Возможные вопросы на собеседовании
Проверка опыта проектирования на высоком уровне и понимания долгосрочных последствий архитектурных решений.
Опишите ваш опыт разработки корпоративной модели данных (EDM). С какими основными сложностями вы столкнулись при масштабировании?
Staff-инженер должен уметь внедрять стандарты качества и наблюдаемости в масштабах всей организации.
Как вы подходите к обеспечению качества и наблюдаемости (observability) данных в сложных пайплайнах? Какие инструменты и метрики вы считаете критическими?
Вакансия требует опыта внедрения RBAC и практик управления данными.
Расскажите о вашем опыте внедрения управления доступом на основе ролей (RBAC) в хранилищах данных. Как вы балансируете между безопасностью и удобством доступа для аналитиков?
Оценка лидерских качеств и умения разрешать технические конфликты.
Приведите пример ситуации, когда вам нужно было убедить руководство или другие команды принять непопулярное, но технически верное архитектурное решение.
Проверка навыков оптимизации и работы с облачными хранилищами.
Какие стратегии оптимизации производительности вы применяли при работе с Amazon Redshift для обработки терабайтных объемов данных?
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