Staff Software Engineer - Infinia Data Engine

Overview

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

  

"DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC 

  

“The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA 

  

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence. 

  

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management. 

  

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage. 

Job Description

We are seeking a Staff Software Engineer to join the Infinia Data Engine team — the group responsible for powering high-performance, AI-native data workflows on DDN’s next-generation distributed data platform.

 

In this role, you will lead the design and optimization of data execution engines, data format handling, and query-layer integration with industry-standard open-source frameworks including Apache Iceberg, Delta Lake, Apache Spark, and others. You’ll play a key role in bridging proprietary high-performance systems with open ecosystems — enabling large-scale, real-time data access, transformation, and analytics.

 

This is a hands-on, high-impact position ideal for an engineer who thrives at the intersection of distributed systems, open-source data technologies, and performance optimization.

Key Responsibilities

Core System Design & Development

• Design and implement optimized execution layers and data query engines that leverage Infinia’s distributed infrastructure.
• Develop internal systems for high-throughput data access and transformation using formats such as Parquet, ORC, and Avro.
• Engineer integration layers that support open interfaces like HDFS, Apache Iceberg, Delta Lake, and Hive Metastore, enabling seamless compatibility with open-source clients.

Performance Optimization & Scaling

• Build and tune execution plans that leverage Infinia’s high-throughput I/O and compute capabilities for large-scale AI and analytics workloads.
• Analyze and optimize performance of distributed query execution, data storage, caching, and memory usage.

Open-Source Collaboration & Innovation

• Contribute to relevant open-source ecosystems, where appropriate, through collaboration, feature integration, or direct code contributions.
• Stay up to date with the evolving open data lake and query engine landscape to guide architectural decisions.

Cross-Functional Collaboration & Leadership

• Partner with Data Scientists, Platform Engineers, and Product Managers to deliver integrated, end-to-end solutions.
• Provide technical leadership, mentorship, and design direction to other engineers on the team.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in software development, with 5+ years in distributed systems, data platforms, or big data technologies.
• Expert-level knowledge of Java, Python, and SQL.
• Deep understanding of file formats including Parquet, ORC, Avro, and their performance characteristics.
• Experience working with Apache Spark,