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Software Engineer Data Infrastructure Kafka Jobs

Cohere

Software Engineer, Data Infrastructure

$117K - $140K/yr

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data layers essential for AI training workloads, collaborating with top researchers and engineers in the ...

Cohere

Software Engineer, Data Infrastructure

New York, NY · On-site

$125K - $150K/yr

As a Software Engineer, Data Infrastructure, you will: * Work directly on petabyte-scale storage infrastructure, and the networking and performance challenges that come with it. * Collaborate daily ...

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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 Jul 20, 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.
More about Software Engineer Data Infrastructure Kafka jobs
What states have the most Software Engineer Data Infrastructure Kafka jobs? States with the most job openings for Software Engineer Data Infrastructure Kafka jobs include:
What job categories do people searching Software Engineer Data Infrastructure Kafka jobs look for? The top searched job categories for Software Engineer Data Infrastructure Kafka jobs are:
Software Engineer Data Infrastructure Kafka jobs near you
Infographic showing various Software Engineer Data Infrastructure Kafka 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.
Principal Software Engineer, Data Infrastructure

Principal Software Engineer, Data Infrastructure

Roblox

San Mateo, CA • On-site

$153K - $206K/yr

Other

Posted 23 days ago

Job description

Roblox's data infrastructure processes petabytes of data daily, powering analytics, ML, and product decisions for a platform serving 200M+ daily active users. As a Principal Software Engineer in our Data Infra org, you will be the primary technical leader driving the strategic vision, long-term architecture, and massive scalability of our distributed data platforms that power Roblox. You will own and drive the next-generation architecture of our core platforms, which span Kafka, Flink, Spark, Trino, Druid, Airflow and Data Catalog. This role operates under high ambiguity, demanding unparalleled ownership to redefine the limits of infrastructure handling exabyte-scale workloads, and providing a unique opportunity to lead the future evolution of our global data ecosystem.

You Will:
  • Define Multi-Year Technical Strategy: Own and drive the end-to-end architectural vision for Roblox's core data platforms spanning Kafka, Flink, Spark, Trino, Druid, Airflow, and Data Catalog systems. Turn multi-year company strategies into concrete, production-grade infrastructure blueprints.
  • Lead Cross-Functional Alignment: Partner closely with executive leadership, platform governance, data science, and product engineering teams across Roblox to align technical roadmaps with business-critical metrics. Act as a trusted technical advisor, ensuring centralized infrastructure meets strict platform requirements.
  • Optimize Performance Engine Internals: Deep-dive into distributed engine internals, complex query planning, state management, serialization efficiency, and advanced memory optimization techniques to maximize throughput and cost-efficiency under peak compute loads.
  • Pioneer Autonomous Agentic Interfaces: Spearhead the integration of advanced AI/ML capabilities and large language models (LLMs) within our core data platform to deliver self-serve data discovery, automated metadata generation, and intelligent autonomous interaction layers.
  • Cultivate Engineering Excellence: Set the baseline for code quality, architectural standards, and system robustness across the organization. Mentor staff, senior, and mid-level engineers, fostering a culture of technical rigor, deep-dive post-incident analyses, and proactive chaos engineering validation.
You Have:
  • B.S. equivalent in CS or sufficient experience.
  • 8+ years of experience building, designing, testing and maintaining production-grade, large-scale distributed systems.
  • Data Platform Depth: Expert-level mastery and a deep history of building with foundational data technologies within our tech stack: Kafka, Flink, Spark, Trino, Druid, Hive, Airflow, or advanced Data Catalog / Metadata systems.
  • Infrastructure Core Builder: A proven track record of architecting, writing, and deploying core data platform code and distributed systems from the ground up. We are looking for someone who builds the engine rather than someone who just maintains or configures existing setups. You have driven major structural overhauls and 1-to-N platform evolutions at hyper-scale (100M+ active users).
  • Strong Engineering Foundations: Robust proficiency in Java, Go, or Scala, with a track record of writing clean, highly performant backend code.
  • Cloud Fluency: Proven expertise managing, scaling, and troubleshooting complex stateful and stateless multi-cluster data infrastructure running on top of Kubernetes within AWS or GCP.
  • Cross-Organizational Technical Leadership: A proven track record of influencing technical direction across a large engineering organization, leading consensus on complex architectural initiatives, and championing successful multi-quarter projects.
  • Extreme Ownership: A history of radical accountability. You do not wait for clean specifications in high-ambiguity environments; you actively define the technical requirements, unblock dependencies, rally engineers across pods, and steer complex projects from initial whiteboard sketch all the way to production stability.
Nice to Have:
  • Contributions to open-source projects in the data infrastructure ecosystem.
  • Experience operating infrastructure at consumer-internet scale (100M+ users).

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