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Internship Azure Databricks Jobs in Oregon (NOW HIRING)

Striim, Inc.

OR · On-site

$120K - $130K/yr

Requirements * 1-3 years of professional experience or equivalent graduate research, internships ... Azure, GCP, Databricks, Snowflake, BigQuery, Amazon Redshift, or Azure Synapse. * Experience ...

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Internship Azure Databricks information

What is the difference between Internship Azure Databricks vs Data Engineer Intern?

AspectInternship Azure DatabricksData Engineer Intern
Required SkillsAzure, Databricks, SQL, PythonSQL, Python, ETL, Cloud platforms
Work EnvironmentCloud-based, data analytics projectsData pipelines, database management
CertificationsAzure certifications beneficialBasic data engineering certifications helpful

Internship Azure Databricks focuses on working with the Databricks platform on Azure for data analytics, while Data Engineer Interns work on building data pipelines and managing data infrastructure. Both roles require knowledge of SQL and Python, but Azure Databricks emphasizes cloud-based analytics, making it ideal for those interested in cloud data solutions.

What is an Azure Databricks internship?

An Azure Databricks internship is a temporary, hands-on role for students or recent graduates to gain practical experience working with Azure Databricks, a cloud-based data analytics platform. Interns typically assist with data engineering, data analytics, or machine learning projects using tools such as Apache Spark within the Azure environment. The internship helps participants develop technical skills, learn about big data processes, and contribute to real-world business solutions under the guidance of experienced professionals.

What are the key skills and qualifications needed to thrive as an Azure Databricks intern?

To thrive as an Azure Databricks Intern, you need a solid understanding of data analytics, programming (especially Python or Scala), and foundational knowledge of cloud computing concepts. Familiarity with Databricks, Azure cloud services, SQL, and possibly certifications like Microsoft Azure Fundamentals are typically beneficial. Strong problem-solving abilities, eagerness to learn, and effective communication skills help you collaborate with teams and adapt quickly in a fast-paced environment. These skills enable you to efficiently process and analyze data, contribute to projects, and make the most of your internship experience.

What are some common challenges faced during an Azure Databricks internship, and how can I prepare for them?

As an Azure Databricks intern, you may encounter challenges such as learning to navigate the Databricks workspace, understanding distributed data processing with Spark, and collaborating across multidisciplinary teams. To prepare, it's helpful to familiarize yourself with cloud computing basics, Python or Scala programming, and foundational data engineering concepts. You'll often work closely with data engineers and analysts, so strong communication and a willingness to ask questions are key to overcoming initial hurdles and making the most of your learning experience.
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Internship Azure Databricks jobs near you

Junior Solutions Architect - MLOps & Real-Time Data Integration

Striim, Inc.

OR • On-site

$120K - $130K/yr

Other

Medical, Dental, Vision, PTO

Posted 11 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.

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