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Big Data Engineer Intern Jobs in Oregon (NOW HIRING)

Nagarro

We are a digital product engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale - across all devices and ...

Nagarro

We are a digital product engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale - across all devices and ...

Netflix

Data Engineer (L5)

OR · On-site +1

$380K - $610K/yr

Data Engineering at Netflix is a role that requires building systems to process data efficiently ... big data technologies like Spark or Flink and comfortable working with web-scale datasets You have ...

Cotiviti

Data Engineer - AI

$101K - $132K/yr

Using their technical experience in ETL processes, Data Engineers ensure operational functions are ... Any Databricks / AWS certifications is a big plus. * Familiarity with data pipeline orchestration ...

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Big Data Engineer Intern information

What are the key skills and qualifications needed to thrive as a Big Data Engineer Intern, and why are they important?

To thrive as a Big Data Engineer Intern, you need a solid understanding of programming (especially Python, Java, or Scala), data structures, and basic knowledge of distributed computing concepts, typically supported by coursework or relevant projects. Familiarity with big data tools like Hadoop, Spark, and data querying languages such as SQL, as well as exposure to cloud platforms like AWS or Azure, is highly valuable. Strong analytical thinking, problem-solving abilities, and communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills and qualities are crucial for handling large-scale datasets and supporting the development of data-driven solutions within engineering teams.

What does a Big Data Engineer Intern do?

A Big Data Engineer Intern assists with designing, building, and maintaining large-scale data processing systems. They often work with technologies such as Hadoop, Spark, and SQL to manage and analyze large datasets. Interns may help develop data pipelines, clean and organize data, and support senior engineers in optimizing data workflows. This role provides hands-on experience in handling big data tools and working on real-world data engineering projects.

What is the difference between Big Data Engineer Intern vs Data Engineer?

AspectBig Data Engineer InternData Engineer
CredentialsRelevant coursework, some internshipsBachelor's or master's in CS, experience preferred
Work EnvironmentInternship, learning-focused, entry-level projectsFull-time, professional projects, team collaboration
Industry UsageTech, finance, healthcare, startupsSame industries, more responsibility
Search & Comparison IntentEntry-level, internship opportunitiesCareer advancement, full-time roles

The main difference between a Big Data Engineer Intern and a Data Engineer is experience level and responsibility. Interns are typically students or early learners gaining exposure, while Data Engineers are full-time professionals managing complex data systems. Internships serve as stepping stones toward full-time data engineering careers.

What are some common challenges a Big Data Engineer Intern might face when working with large datasets?

As a Big Data Engineer Intern, you'll often encounter challenges related to managing the scale and complexity of massive datasets. These can include optimizing data ingestion pipelines for speed and efficiency, troubleshooting data quality issues, and ensuring data privacy and security. Additionally, you may need to quickly learn new tools or frameworks, such as Hadoop or Spark, and collaborate closely with data scientists and engineers to ensure data is structured and accessible for analysis. Developing problem-solving skills and being proactive in seeking help from your team can help you overcome these hurdles.
Big Data Engineer Intern jobs near you

Big Data Engineer

Avani Technology Solutions, Inc.

Hillsboro, OR • On-site

$58 - $76.75/hr

Full-time

Re-posted 27 days ago

Job description

  • Expert in Spark, Python scripting and strong in SQL
  • 5+ years processing large datasets on big data platform such as SPARK; Python EMR; Hadoop on AWS
  • 5+ years of experience architecting and building scalable Reporting and Advance Analytics solutions using Big Data technologies
  • Hands-on experience AIRFLOW; GLUE; AWS DataPipeline or similar services on AWS
  • Experience with Database solutions on cloud such as Redshift or Snowflake is preferable.
  • Proven experience building libraries, user defined functions and frameworks on Big Data Platform.
  • Experience with performance/scalability tuning, algorithms and computational complexity

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