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Software Engineer Data Infrastructure Kafka Jobs

Gamma

Software Engineer, Data Systems

San Francisco, CA · On-site

$134K - $162K/yr

... Kafka ingestion through Snowflake analytics, setting technical direction for data infrastructure ... Required : • 10+ years as a data or software engineer with deep expertise in distributed systems ...

Gamma

Software Engineer, Data Systems

San Francisco, CA · On-site

$134K - $162K/yr

... Kafka ingestion through Snowflake analytics, setting technical direction for data infrastructure ... years as a data or software engineer with deep expertise in distributed systems, data ...

CoreWeave

Software Engineer - Data Infrastructure Services

$117K - $140K/yr

... data protection regulation. Qualifications : Required : • 2~5 years of experience in a software or infrastructure engineering industry. • Experience operating services in production and at scale ...

HeyGen

Software Engineer, Data

Los Angeles, CA · On-site

$180K - $220K/yr

... Kafka) that ingest and transform massive multi-modal data-text, audio, and video-to train and run ... Data Lakehouse Infrastructure: Architect and manage data lakehouse solutions (e.g., Snowflake ...

Sift

Staff Software Engineer, Data

San Francisco, CA · On-site

The Staff Software Engineer, Data will design and build scalable data infrastructure to support ... Kafka Streams, Beam, or similar • Proficiency with relational and time-series databases like ...

Sift

Staff Software Engineer, Data

El Segundo, CA · On-site

The Staff Software Engineer, Data will design and build scalable data infrastructure to support ... Kafka Streams, Beam, or similar • Proficiency with relational and time-series databases like ...

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All JobsSoftware Engineer Data Infrastructure Kafka Jobs

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.
Software Engineer, Data Infrastructure

Software Engineer, Data Infrastructure

Scale AI

Washington, DC • On-site

Full-time

Posted 27 days ago

Scale AI rating

8.1

Company rating: 8.1 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

95th of 209 rated software companies

Job description

Job Summary:
Scale AI is seeking a highly skilled and motivated Mission Software Engineer to join their dynamic Federal Engineering team. In this role, you will architect and build foundational data infrastructure that serves as the brain of a project ecosystem, developing onsite solutions for government customers and ensuring seamless integration with existing workflows.
Responsibilities:
• Architect the Data Ensemble: Design and implement the architecture to ensemble various sources of injected context (deeply structural simulation data, historical game states, and dynamic user inputs) into a unified, highly queryable format optimized for LLM consumption.
• Massive Batch Infrastructure: Build highly scalable, resilient data architectures from scratch. You will optimize for moving, transforming, and processing massive quantities of simulation output data via enormous batch jobs, maintaining the minimal latency required for rapid wargame iterations.
• Complex Data Modeling: Design sophisticated, highly relational data models that accurately represent massive, state-based simulation environments, making them easily interpretable by machine learning models.
• First-Principles Problem Solving: Navigate highly ambiguous product requirements to design custom, ground-up systems where existing open-source or enterprise tools simply cannot handle the structural complexity or scale.
• Technical Leadership: Set the technical standard for the data infrastructure team, driving rigorous code quality, system performance, and architectural clarity.
Qualifications:
Required:
• 5+ years of backend or data infrastructure experience, operating at a Senior, Staff, or Principal level.
• Deep, expert-level proficiency in systems languages (e.g., Rust, Go, C++, or highly optimized Python/Java, Spark) and a fundamental understanding of memory management, compute limits, and distributed systems architecture.
• Proven track record of processing massive datasets. You understand how to optimize massive batch jobs and parallel processing across distributed simulation nodes without sacrificing speed.
• You must be an expert in surfacing the right needle from an ocean of hay to feed decision-making engines.
• A strong desire to build robust, foundational technology that supports national security and defense modernization.
Preferred:
• An active Secret or TS/SCI clearance is a nice to have for this role. If you do not have an active clearance, you must be eligible and willing to obtain one.
• Experience with LLM context optimization, vector embeddings, or agentic AI frameworks (e.g., advanced RAG architectures).
• Deep domain experience working with wargaming data, complex systems modeling, or distributed simulation protocols.
• Previous experience in a high-growth, 0-to-1 startup environment.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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