20 часов назад
Data Engineer (AWS)
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 Engineer (AWS): Building modern cloud-native data and AI platforms for startups and enterprise customers with an accent on scalable lakehouse architectures, ETL/ELT pipelines, and real-time data services. Focus on designing RAG and vector search integrations, modernizing legacy ETL systems, and improving platform reliability through governance, observability, and performance tuning.
Company
provides AI-led professional and managed cloud services, specializing in AWS and Salesforce migrations, implementations, and ongoing platform management for organizations globally.
What you will do
- Design and build scalable cloud-native data platforms and lakehouse architectures on AWS.
- Develop and maintain ETL/ELT pipelines, streaming architectures, and data services.
- Apply data modeling, orchestration, governance, and observability practices.
- Help architect AI solutions, including RAG pipelines, vector search, and ML integrations.
- Translate customer business requirements into functional technical designs with internal teams.
- Support code reviews, troubleshooting, performance tuning, production operations, and migration from legacy ETL systems to cloud data warehouses.
Requirements
- 4–6 years of hands-on experience in Data Engineering, Data Architecture, or Backend Engineering.
- Experience implementing cloud-native architectures and AWS data services.
- Hands-on experience with at least 4–5 of Databricks, DBT, Snowflake, Airflow, Kafka, Spark, Redshift, S3, AWS Glue, or Lambda.
- Advanced SQL and Python skills.
- Experience designing data warehouses and lakehouse architectures and building scalable real-time data pipelines.
- Understanding of CI/CD, Infrastructure as Code, monitoring, customer communication, and technical ownership.
Nice to have
- Experience with Amazon Bedrock, SageMaker, or vector databases.
- Exposure to Kubernetes or microservices architectures.
- Experience in high-scale fintech, gaming, or retail environments.
- Professional Services or Managed Services experience.
- Familiarity with data quality and observability frameworks.
Culture & Benefits
- Learning and personal development supported by experienced leaders.
- Competitive salary and bonus incentives.
- Benefits, flexible hours, and mentoring.
- Collaborative work with customers and internal technical teams.
Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →