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DDN is seeking an engineering leader to build and optimize high-performance data ingestion, transformation, and streaming frameworks for their Infinia Data Engine, which is a foundational layer of DDN's AI-native data platform. This role aims to enable the world's most demanding AI and analytics workloads by delivering scalable, cloud-agnostic data pipelines and seamless integration with modern open-source ecosystems.

Requirements

• 10+ years of engineering experience in data infrastructure, distributed systems, or large-scale analytics platforms.
• Deep technical expertise in open-source data frameworks such as Trino, Delta Lake, Apache Iceberg, Ray Data, or Mosaic Streaming.
• Strong understanding of data ingestion, transformation, streaming, and orchestration for AI and real-time workloads.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and hybrid deployment architectures.
• Proficiency in distributed computing, parallel data processing, and system-level performance optimization.
• Familiarity with data lakehouse architectures, vectorized query engines, and high-throughput data connectors.
• Understanding of AI/ML pipeline integration, data lineage, or model-aware data orchestration.

Responsibilities

• Build, scale, and lead a high-performing team of engineers focused on data ingestion, transformation, and streaming components within the Infinia platform.
• Drive the design and implementation of high-performance, cloud-optimized connectors that integrate with industry-standard open-source tools.
• Oversee the development of end-to-end data workflows that power AI/ML model training, inferencing, and real-time analytics at scale.
• Architect and refine a robust, low-latency data engine that supports diverse formats, compute engines, and workloads across on-prem and multi-cloud deployments.
• Benchmark and optimize data pipelines to meet the extreme throughput and concurrency demands of modern AI applications.
• Champion platform-wide initiatives around data interoperability, metadata management, partitioning strategies, and workload-aware scheduling.
• Ensure the reliability, performance, and security of all data engineering components.

Other

• Proven track record of building and leading high-performance engineering teams.
• Excellent cross-functional collaboration and technical communication skills.
• Experience contributing to or leading open-source software initiatives.
• Remote candidates in the following metropolitan areas: Boston, MA; Raleigh, NC; Denver, CO; or Tucson, AZ.
• Occasional in-person meetings or team events may be required.