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Data Engineer Internship Amazon Jobs in Oregon (NOW HIRING)

... as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud ... DevOps pipelines - Implementing data security practices using AWS, Azure, GCP, Snowflake or ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

Amazon does not sponsor for immigration, including for H-1B, TN, and other non-immigrant visas, for this role. NOTE: Lump sum stipend will be provided to eligible candidates who relocate for this ...

You'll play a pivotal role in maintaining the heartbeat of Amazon Web Services' physical ... The Data Center Chief Engineer (CE) is responsible for ensuring that all electrical, mechanical ...

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Data Engineer Internship Amazon information

What does a data engineer intern do at Amazon?

A Data Engineer Intern at Amazon works on designing, building, and maintaining scalable data pipelines and systems to support business analytics and decision-making. Interns typically collaborate with experienced data engineers and other team members to process large datasets, ensure data quality, and optimize performance. They may also help automate data collection, transformation, and storage processes, gaining hands-on experience with Amazon's cloud technologies and big data tools. The internship offers an opportunity to develop technical skills in databases, programming, and data modeling in a real-world, fast-paced environment.

What are the key skills and qualifications needed to thrive as a data engineer intern at Amazon?

To thrive as a Data Engineer Intern at Amazon, you need a solid understanding of data structures, algorithms, and proficiency in programming languages such as Python, Java, or Scala, often supported by progress towards a degree in computer science or a related field. Familiarity with SQL, cloud platforms (especially AWS), and big data tools like Hadoop or Spark is typically required. Strong problem-solving skills, eagerness to learn, and effective communication help interns collaborate and adapt in a fast-paced environment. These skills and qualities are crucial to efficiently manage data pipelines, contribute to impactful projects, and succeed within Amazon’s data-driven culture.

What types of projects and technologies do data engineer interns at Amazon typically work with?

As a Data Engineer Intern at Amazon, you can expect to work on projects involving large-scale data pipelines, data warehousing, and analytics solutions. Interns often gain hands-on experience with Amazon Web Services (AWS) tools such as Redshift, S3, and Glue, as well as programming languages like Python and SQL. You'll collaborate closely with software engineers, data scientists, and business analysts to design and optimize data systems that support Amazon's business operations. This role provides a strong foundation in both the technical and collaborative aspects of data engineering, offering ample learning opportunities in a fast-paced, innovative environment.

What is the difference between Data Engineer Internship Amazon vs Data Analyst Internship Amazon?

AspectData Engineer Internship AmazonData Analyst Internship Amazon
Required SkillsSQL, Python, ETL, data modelingSQL, Excel, data visualization tools
Work EnvironmentData pipelines, backend systems, cloud platformsData reporting, dashboards, business insights
Industry UsageTech, e-commerce, cloud servicesBusiness, marketing, finance

Both internships are common in Amazon's data teams but focus on different aspects. Data Engineer Internships involve building and maintaining data infrastructure, while Data Analyst Internships focus on analyzing data to generate insights. Candidates should choose based on their technical skills and career interests.

What cities in Oregon are hiring for Data Engineer Internship Amazon jobs?

Cities in Oregon with the most Data Engineer Internship Amazon job openings:

Data Engineer (GovCon | Public Trust Eligibility)

Attain Talent

OR • On-site, Remote

$114K - $137K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Job description

This position supports a federal client and requires US citizenship for Public Trust eligibility

Attain Talent is searching for talented data engineers for our GovCon client. This is a full time position with benefits, and our client partners with federal agencies to build secure, scalable, and mission-driven solutions that make a meaningful impact on millions of people. Recognized by The Washington Post as a Top Workplace in 2025 and 2026. 

About the Role

We are seeking a Data Engineer to design, build, and maintain scalable, efficient data pipelines and systems following modern data engineering best practices. The Data Engineer will partner with other Data Engineers to evaluate and prototype new tools and technologies, assessing their risks and benefits to deliver exceptional value to our clients. 

You Will Get To

  • Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data models using Python, Apache Spark (PySpark), Databricks, dbt, SQL (PostgreSQL), and AWS Glue.
  • Develop and optimize AWS-native data platforms leveraging AWS Glue, Amazon EMR, Amazon MWAA (Apache Airflow), Lambda, Step Functions, Amazon S3, Redshift, RDS, DMS, and CloudWatch.
  • Build high-performance ingestion, transformation, and orchestration workflows for structured and semi-structured data using Apache Iceberg, Parquet, ORC, and Avro.
  • Design and optimize analytical data platforms using Amazon Athena, Trino, Hive, OpenSearch, and enterprise data catalog technologies.
  • Integrate enterprise and external data sources across relational and NoSQL platforms including PostgreSQL, Oracle, Redshift, GraphDB, and other NoSQL databases.
  • Build AI-enabled data solutions using Amazon BedrockRAG pipelines, and vector search technologies including Amazon S3 Vector and OpenSearch vector indexes.
  • Develop cloud infrastructure using CloudFormation (Infrastructure as Code)GitHubHarness, and enterprise CI/CD pipelines while leveraging SNSSQS, and EventBridge for event-driven architectures.
  • Improve the reliability, scalability, performance, and maintainability of enterprise data platforms through monitoring, troubleshooting, automation, and continuous optimization.
  • Support mission-critical analytics and reporting solutions within large-scale AWS-based federal data environments, implementing solutions that comply with FedRAMP and NIST 800-53 security controls.
  • Lead modernization initiatives migrating legacy platforms including IBM DataStageHadoopRunDeck, and shell-based workflows to cloud-native AWS services.
  • Mentor junior engineers through technical guidance, architecture discussions, and code reviews while promoting engineering best practices.
  • Collaborate with cross-functional teams in an Agile environment to define requirements, deliver high-quality data solutions, and communicate technical concepts effectively to technical and non-technical stakeholders.

Who You Are

  • A strategic data engineer who enjoys designing complex systems and solving complex challenges
  • Strong in modern cloud-based solution design
  • Comfortable balancing business needs with technical constraints and long-term strategy
  • A strong communicator 
  • Collaborative, proactive, and comfortable navigating ambiguity

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related technical field
  • 4+ years of professional experience in data engineering or related domains
  • Strong hands-on experience with:
    • DatabricksApache Spark (PySpark)PythonSQL (PostgreSQL), and dbt for large-scale data engineering, ETL/ELT development, data transformation, and data modeling.
    • Designing, building, and maintaining AWS-native data platforms using AWS GlueAmazon EMRAmazon MWAA (Apache Airflow)AWS LambdaAWS Step FunctionsAmazon S3Amazon RedshiftAmazon RDSAWS DMS, and Amazon CloudWatch.
    • Developing scalable data pipelinesworkflow orchestration, and data integration solutions across enterprise environments.
    • Working with modern data lake technologies including Apache Iceberg and data formats such as ParquetORC, and Avro.
    • Designing and optimizing solutions using relational and NoSQL databases including PostgreSQLRedshiftOracleGraphDB, and other NoSQL platforms.
    • Building reliable, high-performance data platforms through performance tuningsystem optimization, and enterprise-scale ETL/ELT architectures.
    • Java development and modern CI/CD practices using Harness.
  • Strong analytical and problem-solving skills
  • Experience working in agile, iterative software development environments
  • Ability to quickly learn and apply new technologies and domain knowledge
  • Excellent written and verbal communication skills, with the ability to explain complex topics to diverse audiences

Nice to Have

  • Experience supporting analytics, data engineering, or modernization initiatives for financial regulators, capital markets, or other highly regulated environments is a plus. 
  • Experience with Kafka (streaming/data pipelines)
  • Experience with Docker and Kubernetes for containerization and orchestration
  • Proficiency with Splunk for log aggregation and system monitoring
  • Experience using Terraform for infrastructure automation and management
  • Strong SQL skills, including performance tuning and complex query design

Full Time Employee Benefits

  • Remote Work (Hybrid roles will be specified in the job post)
  • Competitive Compensation Package
  • Medical, Dental, and Vision
  • Life Insurance, Short/Long Term Disability
  • Employee Assistance Program
  • 401(k) with 4% matching
  • Liberal PTO vacation policy
  • Generous Annual Continuing Education
  • Annual Wellness Budget
  • Bonus Incentive Programs (Employee referrals and performance-based rewards)