Senior Data Engineer - Data Lead

About the role

Foundry Robotics is building an AI-native robotics manufacturing company focused on deploying advanced assembly and production capability for leading robotics companies and national-security-critical hardware. Basically, we're building robots that build robots. We are reimagining manufacturing through advanced robotics. Our mission is to rebuild the American manufacturing industry as an AI-first, assembly-focused, dual-use contract manufacturer. We aim to empower manufacturers with intelligent, efficient, and adaptable robotic systems that redefine productivity and quality. We are hiring a Sr Data Engineer / Data Lead to own the data layer that powers Factory OS. You will design and operate petabyte-scale data pipelines that ingest visual, telemetry, and manufacturing data from the factory floor, move it reliably across edge, on-prem, and cloud environments, and make it available for ML training, analytics, and operational decision-making. You will define the data roadmap-architecture, governance, lifecycle, and tooling-and be the person the rest of the engineering org depends on for clean, reliable, well-modeled data. You will also contribute to backend services where data meets application logic. This is a hands-on engineering role. You will ship.

Responsibilities

• Petabyte-Scale Data Pipelines
• Design, build, and operate PB-scale data pipelines for ingesting, curating, indexing, and preparing manufacturing, visual, and telemetry data
• Implement reliable data movement across embedded, edge, on-prem, and cloud compute environments
• Build streaming and batch processing systems that handle high-throughput factory-floor data in real time
• Implement data lifecycle management: retention, archival, compaction, and cost optimization at scale
• Data Architecture + Roadmap
• Define and own the Factory OS data roadmap-architecture, governance, quality, and tooling strategy
• Design data models, schemas, and contracts that serve application, ML, and analytics consumers
• Establish data cataloging, lineage tracking, and discoverability across the platform
• Drive data quality standards: validation, monitoring, alerting, and anomaly detection
• Evaluate and adopt data technologies (warehouses, lakehouses, streaming platforms) as the platform scales
• Backend Services + Integration
• Contribute to backend services where data pipelines meet application logic (APIs, event-driven systems, database layers)
• Partner with ML engineers to ensure training and inference pipelines have access to clean, well-prepared datasets
• Collaborate with full-stack developers, robotics teams, and operations to translate data needs into reliable infrastructure
• Implement observability: metrics, logging, and tracing across data systems

Requirements

• Between 5-7 years of experience in data engineering, with demonstrated work at terabyte-to-petabyte scale
• Deep hands-on experience with data pipeline frameworks (Spark, Flink, Kafka, Airflow, dbt, or similar)
• Strong proficiency in Python and SQL; backend experience in Go, Java, or TypeScript is a plus
• Experience designing data architectures spanning streaming, batch, lakehouse, and warehouse patterns
• Solid understanding of distributed systems, storage engines, and data modeling (relational and NoSQL)
• Experience with cloud data services (AWS S3/Glue/Redshift, GCP BigQuery/Dataflow, or Azure equivalents)
• Comfortable defining roadmaps, making architectural decisions, and driving alignment across teams
• Comfortable operating independently and owning complex systems end-to-end
• Nice to Have (Not Required)
• Experience with visual or image data pipelines at scale (video ingestion, frame extraction, annotation workflows)
• Background in manufacturing, robotics, or industrial IoT data systems
• Familiarity with ML data preparation workflows (feature stores, dataset versioning, labeling pipelines)
• Experience with edge-to-cloud data architectures and intermittent connectivity patterns
• Exposure to infrastructure-as-code (Terraform, Pulumi) and container orchestration (Kubernetes)
• Growth Opportunities
• Define the entire data architecture and roadmap for an AI-native factory
• Work with petabyte-scale visual, telemetry, and manufacturing data in a real production environment
• Grow into a data leadership role as the team and platform scale
• Direct influence on how data drives quality, throughput, and cost improvements in physical manufacturing
• Why Join Us?
• This is one of the only places where world-class manufacturing operators, mechanical engineers, robotics researchers, and software engineers sit in the same room - building production systems together.
• We are committed to being deeply embedded in the U.S. industrial base. Our focus is simple: build adaptive robotic assembly systems that make American manufacturing scalable, resilient, and competitive again.
• If you want to run a mature, well-defined commercial org, this may not be the role.
• If you want to build the commercial engine th

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