Senior Data Engineer - Data Lead

📋 Description

• • Foundry Robotics is at the forefront of revolutionizing American manufacturing by building an AI-native, assembly-focused, dual-use contract manufacturer. We are developing advanced robotic systems designed to deploy sophisticated assembly and production capabilities for leading robotics companies and critical national-security hardware. Essentially, we are creating the next generation of robots that will build other robots, aiming to empower manufacturers with intelligent, efficient, and adaptable systems that redefine productivity and quality standards.
• • As a Senior Data Engineer / Data Lead, you will be instrumental in owning and shaping the data layer that underpins our innovative Factory OS. This pivotal role involves the design, development, and operation of petabyte-scale data pipelines. These pipelines will be responsible for ingesting a diverse range of data, including visual, telemetry, and manufacturing data, directly from the factory floor. You will ensure the reliable movement of this data across various environments – from embedded systems and edge devices to on-premise infrastructure and cloud platforms. The ultimate goal is to make this data readily accessible and optimized for critical applications such as machine learning training, in-depth analytics, and crucial operational decision-making. Your expertise will be vital in defining the comprehensive data roadmap, encompassing architecture, governance, lifecycle management, and the selection of appropriate tooling. You will become the central point of contact and the go-to expert for the entire engineering organization, ensuring the availability of clean, reliable, and well-modeled data. Furthermore, this role offers the opportunity to contribute to backend services, particularly at the intersection where data pipelines converge with application logic, making it a truly hands-on engineering position where you will be expected to deliver tangible results.
• • Your day-to-day responsibilities will be multifaceted and critical to the success of our data infrastructure. You will be tasked with designing, building, and operating petabyte-scale data pipelines, meticulously handling the ingestion, curation, indexing, and preparation of manufacturing, visual, and telemetry data. A key focus will be on implementing robust and reliable data movement strategies across embedded, edge, on-premise, and cloud compute environments, ensuring seamless data flow regardless of location. You will also be responsible for building sophisticated streaming and batch processing systems capable of managing high-throughput factory-floor data in real time, ensuring immediate insights and responsiveness. Implementing comprehensive data lifecycle management strategies, including retention policies, archival procedures, compaction techniques, and cost optimization at scale, will be crucial for maintaining efficiency and managing resources effectively. Furthermore, you will define and own the Factory OS data roadmap, establishing the overarching architecture, governance framework, quality standards, and tooling strategy. This includes designing effective data models, schemas, and contracts that cater to the diverse needs of application, ML, and analytics consumers, ensuring data is structured for maximum utility. You will also establish systems for data cataloging, lineage tracking, and discoverability across the entire platform, promoting transparency and ease of access. Driving data quality standards through rigorous validation, continuous monitoring, proactive alerting, and anomaly detection will be a core responsibility, ensuring the integrity and reliability of our data assets. As the platform evolves, you will be expected to evaluate and adopt new data technologies, such as warehouses, lakehouses, and streaming platforms, to support our scaling needs.
• • Beyond pipeline management, you will contribute significantly to backend services, particularly where data pipelines intersect with application logic. This includes developing APIs, implementing event-driven systems, and managing database layers. A crucial aspect of this role is partnering closely with ML engineers to guarantee that their training and inference pipelines have access to clean, meticulously prepared datasets, fostering efficient model development. You will also collaborate effectively with full-stack developers, robotics teams, and operations personnel to translate complex data needs into reliable and scalable infrastructure solutions. Implementing comprehensive observability across all data systems, including metrics, logging, and tracing, will be essential for monitoring performance and troubleshooting issues proactively.
• • About the team and company: Foundry Robotics is a unique environment where world-class manufacturing operators, mechanical engineers, robotics researchers, and software engineers collaborate closely to build production systems together. We are deeply committed to revitalizing the U.S. industrial base by creating adaptive robotic assembly systems that make American manufacturing scalable, resilient, and competitive. This is not a role for those seeking to run a mature, well-defined commercial organization; rather, it is for individuals driven to build the commercial engine that will bring AI-driven manufacturing to industrial and energy customers across America.
• • In this role, you will have unparalleled opportunities for growth and impact. You will have the chance to define the entire data architecture and roadmap for an AI-native factory, shaping its future from the ground up. You will gain invaluable experience working with petabyte-scale visual, telemetry, and manufacturing data in a live, production environment. As the team and platform expand, you will have the opportunity to grow into a significant data leadership role, guiding the data strategy and team. Your contributions will directly influence how data drives improvements in quality, throughput, and cost-efficiency within physical manufacturing processes, offering a unique blend of software engineering and tangible industrial impact.