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Intern Streaming Data Engineer Jobs in Raleigh, NC

Jobtailor

Data Solutions Engineer

Durham, NC · On-site

$110 - $160/hr

Bachelor's degree in MIS, Computer Science, Engineering, or equivalent experience * Proficiency ... Data pipeline design (batch & streaming), DLT expectations for data quality, and robust error ...

New

Cigna

Software Engineering Senior Advisor- Hybrid

Raleigh, NC · Hybrid

$119K - $157K/yr

Modern data ecosystems including Data Lakes, Lakehouse, ELT/ETL pipelines, streaming, and batch ... AWS Engineering including API Gateway, Lambda, EC2, S3, IAM, and CloudWatch; Cloud architecture ...

UnitedHealth Group

Senior ETL Test Engineer

Raleigh, NC · Remote

$91K - $163K/yr

  • Retirement

Implement data validation, reconciliation, and anomaly detection logic across batch and streaming ... Bachelor's degree in Computer Science, Engineering, or IT related field * 5 years of experience in ...

UnitedHealth Group

Senior ETL Test Engineer

Raleigh, NC · On-site

$91K - $163K/yr

  • Retirement

Implement data validation, reconciliation, and anomaly detection logic across batch and streaming ... Bachelor's degree in Computer Science, Engineering, or IT related field * 5+ years of experience in ...

AlphaPoint

Senior Wallet Developer

Raleigh, NC · Remote

$55.75 - $73.75/hr

Develop and integrate REST APIs, gRPC, WebSockets, streaming data, and event-driven services. * Build and maintain developer tools, internal services, and automation that improve engineering ...

New

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Intern Streaming Data Engineer information

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

As of Aug 20, 2026, the average hourly pay for intern streaming data engineer in Raleigh, NC is $24.71, according to ZipRecruiter salary data. Most workers in this role earn between $20.10 and $28.03 per hour, depending on experience, location, and employer.

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.

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 are the most commonly searched types of Streaming Data Engineer jobs in Raleigh, NC?

The most popular types of Streaming Data Engineer jobs in Raleigh, NC are:

What are popular job titles related to Intern Streaming Data Engineer jobs in Raleigh, NC?

For Intern Streaming Data Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Intern Streaming Data Engineer jobs in Raleigh, NC look for?

The top searched job categories for Intern Streaming Data Engineer jobs in Raleigh, NC are:

Intern Streaming Data Engineer jobs near you
Infographic showing various Intern Streaming Data Engineer job openings in Raleigh, NC as of June 2026, with employment types broken down into 85% Full Time, 4% Part Time, and 11% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $51,391 per year, or $24.7 per hour.

Data Solutions Engineer

Jobtailor

Durham, NC • On-site

$110 - $160/hr

Other

Posted 2 days ago

New

Job description

Responsibilities
  • Design, implement, and support end‑to‑end ELT pipelines (ingest → transform → publish) in Databricks/ADF
  • Implement data quality checks (DLT expectations, unit tests) with alerting and remediation runbooks
  • Build curated, analytics‑ready Delta tables using dimensional modeling for consumption by BI Developers
  • Implement CDC and deletion‑flag patterns; manage schema drift and partitioning/Z‑Ordering strategies
  • Operationalize jobs with monitoring, logging, alerting; participate in an on‑call rotation as needed
  • Partner with the Data Architect to align designs with standards for governance, security, and cost efficiency
  • Document pipelines, data contracts, and SLAs; continuously improve performance and reliability
Requirements
  • 2+ years of hands‑on data engineering (or comparable software engineering with significant data work)
  • 2+ years building pipelines on Azure and Databricks (or equivalent cloud + Spark)
  • Strong SQL (analytical queries, window functions), PySpark/Spark SQL, and data modeling fundamentals
  • Bachelor’s degree in MIS, Computer Science, Engineering, or equivalent experience
  • Proficiency with SQL and Python (PySpark), including performance tuning on large datasets
  • Experience with Azure Databricks, Delta Lake, Delta Live Tables (DLT), Azure Data Factory (or Fabric Data Pipelines), ADLS Gen2, and Azure DevOps/Git for CI/CD
  • Working knowledge of Unity Catalog and/or Microsoft Purview for governance, lineage, and security
  • Familiarity with data ingestion patterns (files, APIs, JDBC), schema evolution, CDC, and deletion detection patterns
  • Understanding of dimensional modeling to produce analytics‑ready datasets for Power BI
  • Exposure to orchestration/monitoring, cost optimization, alerting, and runbook‑driven operations
  • Data pipeline design (batch & streaming), DLT expectations for data quality, and robust error handling
  • Source control, branching strategies, and CI/CD for data assets (notebooks, jobs, workflows)
  • Practical understanding of privacy, security, and RBAC in cloud data platforms
  • Excellent communication, documentation, and cross‑functional collaboration skills
  • Analytical mindset; bias toward automation and measurable reliability
  • Applicants must be legally authorized to work in the United States and should not require now, or in the future, sponsorship for employment visa sponsorship.
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