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Обязанности и стек AWS, Python, Scala, SQL и Kafka описаны понятно, но фиксированный контракт на семь месяцев и предпочтение офисной работы снижают привлекательность в долгосрочной перспективе.
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Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Engineer (AWS): Building and optimizing scalable data pipelines and cloud-based data processing solutions with an accent on Python, Scala, SQL, AWS EMR, AWS Glue, REST APIs, and Apache Kafka. Focus on designing distributed ETL/ELT architectures, developing real-time streaming systems, troubleshooting complex data pipelines, and ensuring data quality, performance, and scalability.
Location: McLean, VA; onsite work is preferred. Candidates available to work from other designated company locations may also be considered.
Pay rate: $75–$85 per hour, W2 only.
Duration: 7 months.
Company
hirify.global provides staffing and enterprise technology services.
What you will do
Design, develop, maintain, and optimize scalable data pipelines and data processing solutions.
Build ETL/ELT pipelines for data integration, transformation, and processing.
Use AWS EMR and Glue to develop and manage cloud-based data processing solutions.
Develop and integrate REST APIs and build real-time streaming solutions with Apache Kafka.
Write, optimize, and troubleshoot complex SQL queries and data pipeline issues.
Collaborate with cross-functional teams to deliver reliable, performant, and scalable data architectures.
Requirements
5–10 years of professional experience in data engineering or a closely related field.
Strong programming experience with Python and Scala.
Hands-on AWS experience, including AWS EMR and AWS Glue for data processing and ETL development.
Strong SQL skills, including complex queries, data transformations, and performance optimization.
Experience developing and integrating REST APIs.
Hands-on Apache Kafka experience for real-time data streaming and processing.
Experience designing, developing, and maintaining scalable data pipelines; strong understanding of data integration, ETL/ELT processes, and distributed data processing.
Experience working with large datasets in enterprise environments.
Strong analytical, troubleshooting, problem-solving, organizational, and attention-to-detail skills.
Excellent interpersonal, written, and verbal communication skills, with the ability to collaborate across technical teams and manage multiple priorities in a fast-paced environment.
Nice to have
Experience with Artificial Intelligence (AI) or AI-related technologies.
Culture & Benefits
Enterprise environment focused on reliable, efficient, and scalable data solutions.
W2 employment for a fixed seven-month engagement.
Onsite work in McLean, VA is preferred; other designated company locations may be considered.
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