Senior Data Engineer - Data Lead

Foundry Robotics Inc.•San Francisco, CA

1d•$150,000 - $250,000•Onsite

About The Position

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. 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.

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
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 Haves

Backend experience in Go, Java, or TypeScript is a plus
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)

Responsibilities

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
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
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