- Страна
- США
- Зарплата
- 119 000 $ – 129 000 $
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на вакансии с ИИ

Data Engineer (6458)
Привлекательная позиция в инновационной лаборатории с четким фокусом на современные технологии (AI/ML, RAG). Хороший социальный пакет и прозрачный диапазон зарплаты, хотя требование присутствия в офисе 3 дня в неделю может подойти не всем.
Сложность вакансии
Роль требует уверенного владения Python, AWS и фреймворками распределенной обработки данных, а также наличия или возможности получения допуска Secret clearance. Гибридный формат работы в Рестоне добавляет географическое ограничение.
Анализ зарплаты
Предложенная зарплата ($119k - $129k) находится в пределах рыночной нормы для специалиста уровня Middle в регионе Вирджиния, хотя верхняя граница рынка для опытных инженеров может быть выше. Дополнительные бонусы и компенсация обучения повышают общую ценность предложения.
Сопроводительное письмо
I am writing to express my interest in the Data Engineer position at MetroStar. With over 4 years of experience in building scalable ETL/ELT pipelines and a strong background in AWS cloud services, I am confident in my ability to contribute to the MetroStar Innovation Lab. My expertise in Python and distributed processing frameworks like Spark aligns perfectly with your requirements for managing diverse data modalities, from time-series to unstructured video and text.
In my previous roles, I have successfully operationalized data pipelines for machine learning workloads, including RAG and inference systems. I am particularly drawn to MetroStar's mission-driven culture and the opportunity to work on complex projects that bridge the gap between raw data and advanced AI insights. I am eager to bring my technical skills in data warehousing and orchestration to your team and support the growth of your evolving data ecosystems.
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Описание вакансии
As Data Engineer, you’ll design and maintain scalable data pipelines and cloud-based data platforms that support advanced analytics and machine learning workloads. You will also leverage Python, distributed data processing frameworks, and AWS services to ingest, transform, and manage structured and unstructured data across a variety of sources. The ideal candidate will collaborates with engineers and stakeholders to build reliable data architectures, ensuring efficient data access, integration, and performance in production environments.
We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed withour people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers.
If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!
What you’ll do:
- Design and implement data ingestion, transformation, and enrichment pipelines across multiple concurrent projects with varying data modalities (time-series sensor data, video, images, documents, and metadata).
- Develop and manage cloud-native data services including object storage workflows, vector database integration, and structured data warehousing to support multi-modal AI/ML systems.
- Work closely with AI/ML engineers to operationalize data pipelines that feed training, inference, and retrieval-augmented generation (RAG) workloads in production.
- Establish data quality, lineage, and governance practices across projects that are maturing from prototype to product, bringing structure and repeatability to evolving data ecosystems.
- Support the processing and organization of unstructured data (video files, PDFs, technical manuals) into formats suitable for embedding generation, semantic search, and summarization.
- Present technical approaches and data architecture decisions to both technical teammates and non-technical stakeholders.
What you’ll need to succeed:
- Bachelor's Degree in Computer Science, Data Science, Information Systems, Engineering, or a comparable technical discipline.
- An active Secret clearance or the ability to obtain
- 2-4+ years of professional experience in data engineering, data platform development, or a closely related technical role.
- Relevant cloud or data engineering certifications are a plus (e.g., AWS Certified Data Engineer, Databricks Data Engineer Associate, AWS Solutions Architect, or equivalent)
- Strong proficiency in Python for data engineering (scripting, pipeline development, data transformation).
- Experience designing and building ETL/ELT pipelines for structured and semi-structured data in cloud environments.
- Experience with AWS cloud services for data workflows (S3, RDS, DynamoDB, EC2/ECS, and related services).
- Hands-on experience with at least one distributed data processing framework (Databricks, Spark, Dask, Ray, or equivalent).
- Demonstrated ability to work with diverse data modalities (time-series, sensor telemetry, image, video, unstructured text).
- Experience with SQL and data warehousing concepts (schema design, partitioning, incremental processing).
- Strong experience with data pipeline orchestration, scheduling, and monitoring in production environments.
- Experience building data pipelines that ingest, transform, or serve data through RESTful APIs.
- Strong communication skills with the ability to explain data architecture decisions to both ML engineers and non-technical stakeholders.
This role is hybrid, with a requirement to be in our Reston HQ office a minimum of 3 days/week.
SALARY RANGE: $119,000 - 129,000
The salary range for this position is determined based on qualifications, skills, and relevant experience. The final salary offered will be determined based on several factors including:
- The candidate's professional background and relevant work experience
- The specific responsibilities of the role and organizational needs
- Internal equity and alignment with current team compensation
- This role is also eligible for additional compensation, subject to the terms and policies of MetroStar, which may include:
- Performance-based bonuses
- Company-paid training and/or certifications
- Referral bonuses
To apply for this position, please submit your resume via the form below or through our careers page: https://www.metrostar.com/jobs/
Application Deadline: Applications will be accepted on a rolling basis until the position is filled; candidates are encouraged to apply as early as possible for full consideration.
Additional Compensation: This role may also be eligible for bonuses and/or additional incentives based on individual and company performance.
Benefits: All full-time employees are eligible to participate in our benefits programs:
- Health, dental, and vision insurance
- 401(k) retirement plan with company match
- Paid time off (PTO) and holidays
- Parental Leave and dependent care
- Flexible work arrangements
- Professional development opportunities
- Employee assistance and wellness programs
Like we said, we are big fans of our people. That’s why we offer a generous benefits package, professional growth, and valuable time to recharge. Learn more about our company culture codeand benefits. Plus, check out our accolades.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment based on merit and without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, status as a protected veteran, or any other status protected by applicable federal, state, local, or international law.
What we want you to know:
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.
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Навыки
- Python
- AWS
- ETL
- ELT
- SQL
- Amazon S3
- Amazon RDS
- Amazon DynamoDB
- Amazon EC2
- Amazon ECS
- Apache Spark
- Databricks
- Dask
- Ray
- Vector Databases
- RESTful APIs
Возможные вопросы на собеседовании
Проверка опыта работы с облачной инфраструктурой, указанной в вакансии.
Опишите ваш опыт проектирования ETL-процессов с использованием AWS S3, RDS и DynamoDB. Как вы обеспечиваете согласованность данных?
Вакансия делает упор на AI/ML и RAG.
Как бы вы спроектировали пайплайн для обработки неструктурированных данных (например, PDF или видео) для последующего использования в векторной базе данных?
Проверка навыков работы с большими данными.
В каких ситуациях вы предпочтете использовать Spark или Dask вместо стандартных библиотек Python, и с какими проблемами производительности вы сталкивались?
Важный аспект для зрелых продуктов.
Как вы организуете мониторинг качества данных и отслеживание их происхождения (lineage) в производственной среде?
Оценка навыков взаимодействия с командой.
Расскажите о случае, когда вам нужно было объяснить сложное архитектурное решение нетехническому заказчику. Каков был результат?
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- Страна
- США
- Зарплата
- 119 000 $ – 129 000 $