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Software Engineer Data Infrastructure Kafka Jobs

Instacart

Staff Software Engineer, Data Infrastructure

OR · Remote

$114K - $137K/yr

We're looking for a Staff Software Engineer to join our Data Governance and Foundations Team. In ... Experience with event-driven and streaming infrastructure (e.g., Kafka, Flink) for real-time ...

Figma

Software Engineer, Data Infrastructure

San Francisco, CA · On-site +1

$134K - $162K/yr

We'd love to hear from you if you have:5+ years of backend or infrastructure engineering experience ... Strong expertise in batch and streaming data processing technologies such as Spark, Flink, Kafka ...

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Software Engineer Data Infrastructure Kafka information

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$44.5K

$129.7K

$177.5K

How much do software engineer data infrastructure kafka jobs pay per year?

As of Jun 6, 2026, the average yearly pay for software engineer data infrastructure kafka 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 is the difference between Software Engineer Data Infrastructure Kafka vs Data Engineer?

AspectSoftware Engineer Data Infrastructure KafkaData Engineer
Primary FocusDeveloping and maintaining Kafka-based data pipelines and infrastructureDesigning, building, and managing data systems and pipelines across various platforms
Required SkillsKafka, distributed systems, programming (Java, Python), data streamingSQL, ETL, data modeling, cloud platforms, scripting
Work EnvironmentCollaborates with data teams, DevOps, and software developers in tech environmentsWorks with data analysts, data scientists, and business teams in data-driven companies

Both roles involve data infrastructure but differ in scope. Software Engineer Data Infrastructure Kafka specializes in Kafka and streaming data pipelines, while Data Engineers focus on broader data systems and pipelines across multiple platforms. The choice depends on whether the focus is on Kafka-specific infrastructure or comprehensive data system management.

What are the key skills and qualifications needed to thrive as a Software Engineer Data Infrastructure Kafka, and why are they important?

To thrive as a Software Engineer Data Infrastructure Kafka, you need strong programming skills (Java, Scala, or Python), experience with distributed systems, and a solid understanding of data architecture, typically supported by a degree in computer science or a related field. Proficiency in Apache Kafka, stream processing frameworks (e.g., Kafka Streams, Flink), and familiarity with cloud platforms (AWS, GCP, or Azure) are essential, with certifications in cloud technologies or Kafka being advantageous. Excellent problem-solving, collaboration, and communication skills help you work effectively in cross-functional teams and address complex data challenges. These skills and qualities are crucial for building reliable, scalable data pipelines that support business-critical applications.

What does a Software Engineer Data Infrastructure Kafka do?

A Software Engineer Data Infrastructure Kafka specializes in designing, building, and maintaining large-scale data systems that use Apache Kafka for real-time data streaming and processing. This role involves developing robust pipelines, ensuring data reliability and scalability, and supporting the integration of Kafka with other data storage and analytics systems. Engineers in this position also monitor system performance, troubleshoot issues, and implement best practices for security and data management. They work closely with data engineers, application developers, and operations teams to deliver high-quality data solutions.

What are some common challenges faced by Software Engineers working on Data Infrastructure with Kafka, and how can they be addressed?

Software Engineers focusing on Data Infrastructure with Kafka often encounter challenges such as ensuring high availability, managing large-scale data throughput, and maintaining data consistency across distributed systems. Another common hurdle is tuning Kafka for optimal performance under varying workloads. These challenges can be addressed by implementing robust monitoring, practicing careful partitioning and replication strategies, and collaborating closely with DevOps and data engineering teams. Staying updated with Kafka's latest features and best practices also helps in proactively mitigating issues.
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Software Engineer Data Infrastructure Kafka jobs near you
Infographic showing various Software Engineer Data Infrastructure Kafka job openings in the United States as of May 2026, with employment types broken down into 11% Internship, and 89% Full Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Remote Data Platform Engineer - Kafka & Automation

Canonical Group Ltd

Manhattan, NY • On-site, Remote

$126K - $151K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

A global technology company is seeking a Software Engineer - Data Infrastructure - Kafka to work remotely. This role involves developing automation for data platform operations with a focus on Big Data technologies, including Kafka and Spark. Ideal candidates should have hands-on Python experience, a Bachelor's in Computer Science or a STEM field, and a willingness to travel for work events.

The company offers competitive compensation, a personal development budget, and a flexible work environment. #J-18808-Ljbffr

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