updated 25 days ago
Big Data Engineer - Intern (AWS/Spark)
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Job description
Text:
TL;DR
Big Data Engineer - Intern (AWS/Spark): Developing and maintaining big data platforms, data lakes, data warehouses, and end-to-end data pipelines with an accent on Spark, AWS, Airflow, and machine learning platforms. Focus on designing scalable ETL and machine learning pipelines, administering high-scale data infrastructure, and supporting analytics for high-tech manufacturing.
Location: Onsite in Wuxi, China. Travel: None.
Company
develops storage solutions and data technologies for managing large-scale data growth, serving customers and businesses globally.
What you will do
- Help develop and maintain big data platforms, including data lakes, data warehouses, and data integration systems.
- Apply big data architecture and administration expertise across AWS EMR, Hadoop, AWS S3, Databricks, and related technologies.
- Develop and manage Spark ETL frameworks, orchestrate data workflows with Airflow, and support Presto/Trino query development.
- Design, scale, and deploy machine learning pipelines using platforms such as Spark ML, H2O, and KNIME.
- Collaborate with application architects and business subject-matter experts on end-to-end data pipelines and supporting infrastructure.
- Build productive relationships with peer organizations, partners, and software vendors.
Requirements
- Excellent coding skills in one or more programming languages and willingness to learn new technologies.
- Experience or strong skills in large-scale data engineering, cloud technologies, and the Hadoop ecosystem.
- Knowledge of Spark, Hadoop, Hive, Kafka, and EMR.
- Experience with cloud-based big data solutions, data warehouse appliances, data lakes, and machine learning or data science platforms.
- Proficiency in Python, Java, or Scala, along with familiarity with DevOps, continuous delivery, and Agile development.
- Strong communication, collaboration, problem-solving, and learning skills.
Nice to have
- Understanding of microservices and container-based development with Docker and Kubernetes.
- Experience in a software product development environment.
Culture & Benefits
- Collaborative work with business groups and peer engineering organizations.
- Onsite canteen, grab-and-go market, and coffee shop.
- Basketball, badminton, yoga, and group exercise activities.
- Music, dance, photography, literature, and Toastmasters clubs.
- Onsite festivals, celebrations, and community volunteering opportunities.
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