обновлено 13 дней назад
Data Infrastructure Engineer Intern (AI)
800$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Infrastructure Engineer Intern (AI) (AWS/Redshift): Maintaining and improving data warehousing systems and pipelines with an accent on SQL optimization, data validation, and operational automation. Focus on troubleshooting data infrastructure, supporting reliable ETL workflows, and leveraging AI tools to accelerate development and research.
Location: Remote in Peru
Salary: $800 USD monthly gross
Company
is a fintech and retail technology company building interest-free installment payment and shopping solutions for consumers and merchants.
What you will do
- Maintain and improve data warehousing systems using AWS DMS and Redshift.
- Monitor data pipelines, identify issues, and troubleshoot basic problems.
- Write and optimize SQL queries for analytics and data validation.
- Collaborate with engineers and analysts to support data use cases.
- Participate in testing, documentation, and reliability improvements for data systems.
- Automate repetitive manual processes and reduce operational overhead.
Requirements
- Currently pursuing or recently completed a degree in Computer Science, Data Engineering, or a related technical field.
- Basic knowledge of relational databases, including MySQL and Postgres, and NoSQL databases.
- Familiarity with Python, Go, or a similar programming language.
- Interest in data infrastructure, distributed systems, or backend engineering.
- Demonstrated experience with Claude or equivalent large language model tools is required.
- Strong problem-solving, communication, collaboration, and learning skills.
Nice to have
- Exposure to AWS or other cloud platforms.
- Basic understanding of data pipelines, ETL, and data warehousing.
- Interest in Kafka, Kinesis Streams, Flink, or other big data and streaming technologies.
Culture & Benefits
- Full-time remote work.
- Opportunity to learn and explore data ecosystem tools and technologies.
- Collaborative environment with engineers and analysts.
- Opportunities for career advancement in a rapidly growing team.
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