ZipRecruiter

Log In

1

Intern Streaming Data Engineer Jobs (NOW HIRING)

Otter

Software Engineer - Streaming Data

Seattle, WA · On-site

$167K - $230K/yr

Establish and promote best practices in streaming data engineering, data governance, and cloud platforms while optimizing data models for streaming analytics. What we're looking for * 3+ years of ...

Otter

Software Engineer - Streaming Data

Seattle, WA

$167K - $230K/yr

Establish and promote best practices in streaming data engineering, data governance, and cloud platforms while optimizing data models for streaming analytics. What we're looking for * 3+ years of ...

InterSources

Data Engineer

Phoenix, AZ

$113K - $136K/yr

Senior Data Engineer - Azure & Databricks We are seeking a highly skilled Senior Data Engineer to ... You will lead cloud-based data migration efforts, implement batch and streaming solutions, and ...

NAVA Software Solutions

Data Engineer - Remote

Richmond, VA · On-site +1

$113K - $136K/yr

Data Engineer Location: 100% Remote Duration: 12 months Required Qualifications: * 7+ Years ... Kafka, Flink, or Spark Streaming) * 3+ Years Experience in open source frameworks (Spring Boot ...

next page

Showing results 1-20

All JobsIntern Streaming Data Engineer Jobs

Intern Streaming Data Engineer information

See salary details

$13

$25

$38

How much do intern streaming data engineer jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for intern streaming data engineer in the United States is $25.42, according to ZipRecruiter salary data. Most workers in this role earn between $20.67 and $28.85 per hour, depending on experience, location, and employer.

What is the difference between Intern Streaming Data Engineer vs Intern Data Analyst?

AspectIntern Streaming Data EngineerIntern Data Analyst
Required SkillsKnowledge of streaming platforms (e.g., Kafka, Spark Streaming), programming (Python, Java), data pipeline developmentData analysis, SQL, Excel, basic statistical skills
Work EnvironmentDeveloping real-time data pipelines, working with big data toolsAnalyzing stored data, generating reports and insights
Industry UsageTech, finance, e-commerce companies focusing on real-time data processingMarketing, business intelligence, research departments

The Intern Streaming Data Engineer focuses on building and maintaining real-time data pipelines using streaming technologies, requiring programming and big data skills. In contrast, the Intern Data Analyst primarily analyzes stored data to generate insights, emphasizing statistical and reporting skills. Both roles are common in data-driven industries but serve different functions within data management and analysis.

What does an Intern Streaming Data Engineer do?

An Intern Streaming Data Engineer assists in designing, developing, and maintaining systems that process real-time data streams. They typically work with technologies like Apache Kafka, Apache Flink, or Spark Streaming to collect, process, and analyze data as it arrives. Their responsibilities may include writing code, troubleshooting data pipelines, and collaborating with senior engineers to ensure data flows efficiently. The role is ideal for students or recent graduates looking to gain hands-on experience with big data and real-time analytics.

What types of projects or tasks can an Intern Streaming Data Engineer expect to work on during their internship?

As an Intern Streaming Data Engineer, you can expect to work on projects involving the development, testing, and optimization of real-time data pipelines. Typical tasks may include assisting with the integration of streaming platforms like Apache Kafka or AWS Kinesis, writing and debugging code to process large volumes of incoming data, and collaborating with senior engineers to ensure data quality and reliability. You'll often work within a team of data engineers and analysts, gaining hands-on experience with the latest big data tools and contributing to solutions that support real-time analytics and business decision-making.

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

To thrive as an Intern Streaming Data Engineer, you typically need foundational knowledge in computer science, data engineering concepts, and familiarity with real-time data processing. Experience with tools like Apache Kafka, Apache Flink, or Spark Streaming, and programming languages such as Python or Java, is often preferred. Strong problem-solving skills, attention to detail, and effective teamwork and communication abilities help set candidates apart. These skills and qualifications are crucial for efficiently building, maintaining, and troubleshooting streaming data pipelines in dynamic data-driven environments.
More about Intern Streaming Data Engineer jobs
What cities are hiring for Intern Streaming Data Engineer jobs? Cities with the most Intern Streaming Data Engineer job openings:
What are the most commonly searched types of Streaming Data Engineer jobs? The most popular types of Streaming Data Engineer jobs are:
What states have the most Intern Streaming Data Engineer jobs? States with the most job openings for Intern Streaming Data Engineer jobs include:
What job categories do people searching Intern Streaming Data Engineer jobs look for? The top searched job categories for Intern Streaming Data Engineer jobs are:
Intern Streaming Data Engineer jobs near you
Infographic showing various Intern Streaming Data Engineer job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 96% Full Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $52,867 per year, or $25.4 per hour.
Streaming Data Engineer (Kafka & Spark) - Q125

Streaming Data Engineer (Kafka & Spark) - Q125

R2 Technologies Corporation

Alpharetta, GA • On-site

$54.50 - $72/hr

Full-time

Medical, Retirement, PTO

Posted 13 days ago

Job description

Overview:
Streaming Data Engineer (Kafka & Spark)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a skilled Streaming Data Engineer to build real-time data pipelines using Kafka and Spark. This role focuses on designing low-latency event streaming solutions to enable rapid data processing and analytics.
Key Responsibilities
  • Develop real-time data pipelines using Kafka for event streaming and Spark Streaming or Structured Streaming for processing.
  • Design and manage Kafka topics, producers, and consumers to ensure low-latency data flows.
  • Implement scalable streaming architectures to handle high-velocity data with minimal latency.
  • Collaborate with data teams to integrate streaming data into analytics and machine learning workflows.
  • Optimize Spark jobs for performance and reliability in real-time processing environments.
  • Monitor and troubleshoot streaming pipelines to ensure data integrity and system availability.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience as a Data Engineer with a focus on Kafka and Spark Streaming or Structured Streaming.
  • Proficiency in building real-time and low-latency data pipelines using event streaming technologies.
  • Strong understanding of distributed systems and streaming data architectures.
  • Experience with Spark for processing and transforming streaming data in production.

Preferred Qualifications
  • Familiarity with cloud-based streaming services like AWS Kinesis or Azure Event Hubs.
  • Exposure to advanced Kafka configurations for fault tolerance and scalability.
  • Knowledge of monitoring tools like Confluent Control Center or Prometheus for streaming pipelines.

Compensation & Benefits
  • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
  • Opportunities for professional growth and upskilling in AI and cloud technologies.

R2 Technologies Corporation is an equal opportunity employer and values diversity in the workplace.
Skills:
Data Engineer, Kafka, Event Streaming, Spark Streaming, Structured Streaming, Real-Time, Low Latency

Apply