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Internship Aws Redshift Jobs in Oregon (NOW HIRING)

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Internship Aws Redshift information

What does an AWS Redshift intern do?

An AWS Redshift intern typically assists with managing and optimizing cloud-based data warehouses using Amazon Redshift. Their responsibilities may include designing and running queries, monitoring database performance, troubleshooting issues, and supporting data migration projects. Interns gain hands-on experience with big data tools and cloud technologies, often working alongside data engineers or analysts. This role helps build foundational skills in cloud computing, SQL, and data analytics.

What types of projects do interns typically work on during an AWS Redshift internship?

As an AWS Redshift intern, you can expect to work on projects involving data warehousing, analytics, and cloud migration tasks. Common responsibilities include assisting with data modeling, optimizing SQL queries, setting up ETL pipelines, and supporting performance tuning for large-scale data sets. You'll often collaborate with data engineers, analysts, and developers to implement solutions that help the team leverage the power of AWS Redshift. This hands-on experience provides valuable exposure to real-world cloud database management and builds a strong foundation for a career in data engineering or cloud computing.

What are the key skills and qualifications needed to thrive as an AWS Redshift intern, and why are they important?

To thrive as an AWS Redshift Intern, you need a foundational understanding of database management, SQL, and cloud computing concepts, often supported by coursework in computer science or information technology. Familiarity with AWS services, especially Redshift, and experience with data warehousing tools or AWS Cloud Practitioner certification are typically beneficial. Strong analytical thinking, attention to detail, and effective communication help you solve problems, learn quickly, and collaborate with team members. These skills and qualities are crucial for efficiently managing data, supporting cloud-based projects, and contributing to data-driven decision-making in a professional environment.

What is the difference between Internship Aws Redshift vs Data Engineer Intern?

AspectInternship Aws RedshiftData Engineer Intern
Required SkillsBasic knowledge of AWS, Redshift, SQLSQL, Python, ETL processes
Work EnvironmentCloud-based data warehousing projectsData pipeline development in cloud or on-premise
Industry UsageUsed in data analytics, BI, cloud data solutionsData infrastructure, pipeline creation, data management

Internship Aws Redshift focuses on learning cloud data warehousing with Redshift, while Data Engineer Intern involves broader data pipeline and infrastructure tasks. Both roles require SQL skills and familiarity with cloud environments, but Data Engineer Interns typically work on more complex data systems and programming tasks.

What are popular job titles related to Internship Aws Redshift jobs in Oregon?

For Internship Aws Redshift jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Internship Aws Redshift jobs in Oregon look for?

The top searched job categories for Internship Aws Redshift jobs in Oregon are:

What cities in Oregon are hiring for Internship Aws Redshift jobs?

Cities in Oregon with the most Internship Aws Redshift job openings:

Internship Aws Redshift jobs near you
Infographic showing various Internship Aws Redshift job openings in Oregon as of August 2026, with employment types broken down into 34% Internship, and 66% Full Time. Highlights an 84% In-person, and 16% Remote job distribution.

Junior Solutions Architect - MLOps & Real-Time Data Integration

Striim, Inc.

OR • On-site, Remote

$120K - $130K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 26 days ago

Job description

We are seeking a Junior Solution Architect with a strong foundation in data science, MLOps, cloud data platforms, and modern data engineering to help design and implement real-time data integration and AI-enabled architectures. Working alongside experienced Solution Architects and Engineering teams, this role provides an opportunity for an early-career professional to gain hands-on experience designing scalable streaming data solutions that power enterprise AI, cloud modernization, and real-time analytics.

The ideal candidate is eager to apply data science and machine learning concepts to real-world enterprise challenges, expand technical expertise across modern cloud and data technologies, and develop into a trusted technical architect within a collaborative, fast-paced environment.

Responsibilities

  • Design and implement scalable real-time data integration and Change Data Capture (CDC) solutions using the Striim platform.
  • Design streaming data architectures connecting enterprise databases, cloud data platforms, messaging systems, and AI/ML environments.
  • Develop data pipelines that support machine learning workflows, feature engineering, model inference, and real-time AI applications.
  • Build proof-of-concepts, reference architectures, and deployment patterns for enterprise implementations.
  • Configure, optimize, and troubleshoot data pipelines across cloud and hybrid environments.
  • Collaborate with Engineering, Product, and GTM Engineering teams to validate architectural designs, resolve complex technical challenges, and improve platform capabilities.
  • Participate in architecture reviews, implementation planning, and production readiness activities.
  • Create technical documentation, architecture diagrams, and implementation best practices.
  • Evaluate emerging technologies across AI, MLOps, cloud computing, and real-time data streaming.

Requirements

  • 1-3 years of professional experience or equivalent graduate research, internships, or project experience in data science, machine learning, data engineering, cloud engineering, or solution architecture.
  • Strong foundation in data science, including machine learning algorithms, model selection, feature engineering, and the machine learning lifecycle.
  • Understanding of modern MLOps practices, including model deployment, inference, monitoring, versioning, and CI/CD for machine learning applications.
  • Experience or academic exposure to machine learning frameworks and platforms such as MLflow, Kubeflow, Vertex AI, SageMaker, or Azure Machine Learning.
  • Familiarity with modern data integration concepts, including Change Data Capture (CDC), event-driven architectures, and real-time streaming data pipelines.
  • Working knowledge of relational and NoSQL databases, including SQL proficiency and database administration fundamentals.
  • Experience with cloud platforms and modern cloud data ecosystems, including AWS, Azure, GCP, Databricks, Snowflake, BigQuery, Amazon Redshift, or Azure Synapse.
  • Experience programming in Python or Java and working with REST APIs and JSON.
  • Understanding of Docker containers and modern DevOps concepts; familiarity with Kubernetes, Git, and CI/CD pipelines.
  • Strong analytical, troubleshooting, written, and verbal communication skills.
  • Demonstrated curiosity, adaptability, and a passion for learning emerging technologies in AI, cloud computing, and real-time data streaming.
  • Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related technical discipline.

Benefits

  • Competitive salary and pre-IPO stock options
  • Comprehensive health care plans (medical, dental and vision), including medical and dependent FSA
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • The chance to contribute to and shape an upbeat, fully engaged culture

Compensation

$120,000 - $130,000 USD on an annualized basis. In addition to base pay, this role offers the opportunity to earn commission-based rewards.

Applications will be reviewed on a rolling basis and accepted until the position is filled.

Apply