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Streaming Data Engineer Jobs (NOW HIRING)

Otter

Software Engineer - Streaming Data

Seattle, WA · On-site

$130K - $156K/yr

They are seeking a Software Engineer - Streaming Data to lead the development and maintenance of real-time streaming pipelines, ensuring reliable data delivery and collaborating with cross-functional ...

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 ...

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How much do streaming data engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for streaming data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

A senior or specialized streaming data engineer with extensive experience, advanced skills in big data tools like Kafka and Spark, and certifications can earn $500,000 or more annually. Such roles often involve leading large-scale data infrastructure projects and require a deep understanding of real-time data processing environments.

What does a Streaming Data Engineer do?

A Streaming Data Engineer designs, builds, and maintains real-time data pipelines that process continuous data streams. They work with technologies like Apache Kafka, Apache Flink, or Spark Streaming to handle large-scale data ingestion and transformation. Their role involves ensuring low-latency data processing, optimizing system performance, and integrating with data lakes or warehouses. They collaborate with data scientists, analysts, and DevOps teams to enable real-time analytics and decision-making.

Can I make 200K as a data engineer?

Streaming Data Engineers with extensive experience, advanced skills in tools like Kafka and Spark, and working in high-demand industries can reach or exceed a $200,000 annual salary. Salaries vary based on location, company size, and certifications, with senior roles typically earning higher compensation.

What is a streaming data engineer?

A streaming data engineer designs, builds, and maintains systems that process real-time data streams using tools like Apache Kafka, Spark Streaming, or Flink. They focus on ensuring low-latency data flow, data pipeline reliability, and scalability to support live analytics and applications.

What are the key skills and qualifications needed to thrive in the Streaming Data Engineer position, and why are they important?

To thrive as a Streaming Data Engineer, you need expertise in real-time data processing, programming (often in Java, Scala, or Python), and a solid understanding of distributed computing principles, typically supported by a degree in computer science or a related field. Familiarity with tools like Apache Kafka, Apache Flink, or Spark Streaming, and experience with cloud platforms such as AWS or Azure, are commonly required, with certifications in relevant technologies being a plus. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts make someone stand out in this position. These skills are crucial for efficiently building, optimizing, and maintaining robust streaming data pipelines in dynamic and collaborative environments.

What are the typical day-to-day responsibilities of a Streaming Data Engineer?

As a Streaming Data Engineer, your daily tasks often involve designing, building, and maintaining real-time data pipelines, troubleshooting data flow issues, and optimizing system performance for low-latency processing. You’ll regularly collaborate with data scientists, software engineers, and product teams to integrate new data sources and ensure data quality and reliability. Monitoring live data streams, updating infrastructure, and implementing new features or upgrades also form part of the routine. This role is dynamic and hands-on, offering a mix of independent problem-solving and teamwork in fast-paced, data-driven environments.

What engineers make $300,000 a year?

Senior streaming data engineers with extensive experience, advanced skills in big data tools like Kafka and Spark, and often certifications in cloud platforms can earn $300,000 or more annually. Compensation varies based on industry, location, and company size, with some roles in tech giants and finance firms reaching this level.
More about Streaming Data Engineer jobs
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Streaming Data Engineer jobs near you
Infographic showing various Streaming Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 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 7 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

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