---
title: 'Data Engineer (Founding Team) at Fabrion'
canonical: 'https://feeny.ai/job/data-engineer-founding-team-fabrion-san-francisco-33hf28h6rgc7'
type: 'job'
last_seen: '2026-09-08'
---

# Data Engineer (Founding Team) at Fabrion

- **Company:** Fabrion
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-08-11
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.ashbyhq.com/fabrion/007e5984-4ec4-4dbb-9bd8-0e1d2f66c3a4

## Job description

Data/ETL Engineer (Founding Team)

Location: San Francisco Bay Area

Type: Full-Time

Compensation: Competitive salary + early-stage equity

Backed by 8VC, we're building a world-class team to tackle one of the industry’s most critical infrastructure problems.

## ABOUT THE ROLE

We’re building a multi-tenant, AI-native platform where enterprise data becomes actionable through semantic enrichment, intelligent agents, and governed interoperability. At the heart of this architecture lies our Data Fabric — an intelligent, governed layer that turns fragmented and siloed data into a connected ontology ready for model training, vector search, and insight-to-action workflows.

We're looking for engineers who enjoy hard data problems at scale: messy unstructured data, schema drift, multi-source joins, security models, and AI-ready semantic enrichment. You’ll build the backend systems, data pipelines, connector frameworks, and graph-based knowledge models that fuel agentic applications.

If you've worked on streaming unstructured pipelines, built connectors into ugly legacy systems, or mapped knowledge graphs that scale — this role will feel like home.

## RESPONSIBILITIES

- Build highly reliable, scalable data ingestion and transformation pipelines across structured, semi-structured, and unstructured data sources
- Develop and maintain a connector framework for ingesting from enterprise systems (ERPs, PLMs, CRMs, legacy data stores, email, Excel, docs, etc.)
- Design and maintain the data fabric layer — including a knowledge graph (Neo4j or Puppygraph) enriched with ontologies, metadata, and relationships
- Normalize and vectorize data for downstream AI/LLM workflows — enabling retrieval-augmented generation (RAG), summarization, and alerting
- Create and manage data contracts, access layers, lineage, and governance mechanisms
- Build and expose secure APIs for downstream services, agents, and users to query enriched semantic data
- Collaborate with ML/LLM teams to feed high-quality enterprise data into model training and tuning pipelines

## WHAT WE’RE LOOKING FOR

Core Experience:

- 5+ years building large-scale data infrastructure in production environments
- Deep experience with ingestion frameworks (Kafka, Airbyte, Meltano, Fivetran) and data pipeline orchestration (Airflow, Dagster, Prefect)
- Comfortable processing unstructured data formats: PDFs, Excel, emails, logs, CSVs, web APIs
- Experience working with columnar stores, object storage, and lakehouse formats (Iceberg, Delta, Parquet)
- Strong background in knowledge graphs or semantic modeling (e.g. Neo4j, RDF, Gremlin, Puppygraph)
- Familiarity with GraphQL, RESTful APIs, and designing developer-friendly data access layers
- Experience implementing data governance: RBAC, ABAC, data contracts, lineage, data quality checks

Mindset & Culture Fit:

- You’re a system thinker: you want to model the real world, not just process it
- Comfortable navigating ambiguous data models and building from scratch
- Passionate about enabling AI systems with real-world, messy enterprise data
- Pragmatic about scalability, observability, and schema evolution
- Value autonomy, high trust, and meaningful ownership over infrastructure

Bonus Skills

- Prior work with vector DBs (e.g. Weaviate, Qdrant, Pinecone) and embedding pipelines
- Experience building or contributing to enterprise connector ecosystems
- Knowledge of ontology versioning, graph diffing, or semantic schema alignment
- Familiarity with data fabric patterns (e.g. Palantir Ontology, Linked Data, W3C standards)
- Familiar with fine-tuning LLMs or enabling RAG pipelines using enterprise knowledge
- Experience enforcing data access policy with tools like OPA, Keycloak, Snowflake row-level security

## WHY THIS ROLE MATTERS

Agents are only as smart as the data they operate on. This role builds the foundation — the semantic, governed, connected substrate — that makes autonomous decision-making and agent action possible. From factory ERP records to geopolitical news alerts, the data fabric unifies it all.

If you're excited to tame complexity, unify chaos, and power intelligent systems with trusted data — we’d love to hear from you.

## About Fabrion

## Company Overview
- **One-liner**: Fabrion is an AI-native platform and operating system that provides a real-time intelligence layer for industrial manufacturers, transforming complex value chains with agentic AI, knowledge graphs, and data fabrics.
- **Entity Type**: Private – Seed stage (Seed round with one investor)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2025
- **Founders**: Roy Ng (CEO), Kunal B. (CTO & CPO), Christian V. Jordan, Jake Medwell (Board Member) – experienced operators from AWS, Meta, SAP, and Twilio.

## Core Business
- **Primary industries**: Industrial manufacturing, supply chain, enterprise AI
- **Target customers**: B2B – Enterprise industrial manufacturers, OEMs, and tier suppliers
- **Mission/purpose**: “AI will be the operating system for the next industrial era” – building autonomous, governed AI systems that let teams see, decide, and act on complex manufacturing and supply chain data

## Products & Services
- **Fabrion Platform**: An AI-native operating system that ingests, normalizes, and acts on messy, fragmented industrial data. Uses LLMs, knowledge graphs, vector databases, and agentic systems to deliver real-time intelligence.
- **Fabrion AI Lab**: A full-stack vertical AI research platform focused on:
  - Data fabric for AI (metadata-driven cleanse/correlate/stream)
  - Governance-by-design (observable, reversible, compliant AI)
  - Context memory management (short/long-term recall for agents)
  - Industry knowledge graphs (internal data + external signals)
  - Agent mesh architectures (distributed, goal-conditioned agents)
  - Hybrid & multi-cloud infrastructure
  - Custom fine-tuned models (RAG, SLMs, RLHIL, pre-trained enterprise data)

## Market Standing
- **Valuation**: Not disclosed
- **Key metric**: Seed funding round (amount not publicly stated); 1 investor identified (8VC is prominently featured as a partner)
- **Notable investors/partners**: 8VC (lead through “8VC Build” program); partnering with leading OEMs and forward-thinking industrial companies
- **Growth signals**:
  - Workforce of ~7 employees (all founding/early team) with **9 open job postings** across engineering, research, and business development
  - Web traffic growth: +115.2% monthly (4,264 monthly visits)
  - LinkedIn followers: 343 (+7.5% monthly)
  - Founding team has scaled products from zero to hundreds of millions in revenue at previous companies

## Competitive Advantages
- **AI-native from day one** – not a thin wrapper on foundation models; built as a full-stack vertical AI research platform
- **Deep industry partnerships** with OEMs and industrial companies actively modernizing
- **Proven founding team** with experience at AWS, Meta, SAP, and Twilio – domain expertise in manufacturing, logistics, Big Data, SaaS, and enterprise
- **Focus on governance and compliance** – every AI action is explainable, reversible, and measurable, a critical differentiator for regulated industrial environments
- **Knowledge graph + agent mesh approach** – moves beyond static dashboards to autonomous, semi-autonomous agents

## Strategic Focus
- Build autonomous or semi-autonomous AI agents for manufacturing supply chains (self-healing, rebalancing)
- Embed compliance and governance as first-class citizens in the AI stack
- Advance research in data fabrics, context memory, and custom fine-tuned models for industrial verticals
- Expand agentic capabilities from simulation to real-world production environments

## Why Work Here
- **Culture**: “High EQ, low ego, no assholes”; owners not renters; first-principles thinking; win with customer outcomes; score points, not yardage
- **Work modality**: Hybrid – jobs are listed as “In-Office or Remote” with multiple locations (HQ at Pier 5, The Embarcadero, San Francisco; also remote options)
- **Technical stack**: Kubernetes, Keycloak, Python, SQL, Docker, GraphQL, React, TypeScript, Terraform, Snowflake, Neo4j, OpenAI, MLflow, Grafana, Prometheus – cutting-edge AI/ML infrastructure
- **Impact**: Solving mission-critical problems in global trade and manufacturing – value chains representing billions of dollars; opportunity to define a new industrial AI paradigm
- **Team**: Small founding team with deep experience; opportunity to work across engineering, research, and product from the ground up

## Sources
1. [fabrion.com/careers](https://www.fabrion.com/careers)
2. [builtin.com](https://builtin.com/company/fabrion)
3. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/fabrion)
4. [linkedin.com](https://www.linkedin.com/company/fabrionai)
5. [fabrion.com/ai-lab](https://www.fabrion.com/ai-lab)

## Other roles at Fabrion

- [Founding AI Research Lead - Agentic AI Lab](https://feeny.ai/job/founding-ai-research-lead-agentic-ai-lab-fabrion-san-francisco-c251tdtjjvrw) — San Francisco, CA
- [Founding Designer](https://feeny.ai/job/founding-designer-fabrion-san-francisco-zww16cz5wbwb) — San Francisco, CA
- [Data Partnerships Analyst](https://feeny.ai/job/data-partnerships-analyst-fabrion-san-francisco-2h67mf9ssa3z) — San Francisco, CA
- [Business Development Analyst – Auto](https://feeny.ai/job/business-development-analyst-auto-fabrion-san-francisco-4agd1wrm1x3z) — San Francisco, CA
- [ML/AI Research Engineer — Agentic AI Lab (Founding Team)](https://feeny.ai/job/ml-ai-research-engineer-agentic-ai-lab-founding-team-fabrion-san-francisco-m7ry3fmyn2rd) — San Francisco, CA
- [DevOps Engineer (Founding Team)](https://feeny.ai/job/devops-engineer-founding-team-fabrion-san-francisco-rhgsyhr9s3kx) — San Francisco, CA
- [Frontend Engineer (Founding Team)](https://feeny.ai/job/frontend-engineer-founding-team-fabrion-san-francisco-p4nbwzbq1kgq) — San Francisco, CA
- [ML Ops Engineer — Agentic AI Lab (Founding Team)](https://feeny.ai/job/ml-ops-engineer-agentic-ai-lab-founding-team-fabrion-san-francisco-na47hpj9nvs7) — San Francisco, CA
- [Founding Engineer](https://feeny.ai/job/founding-engineer-fabrion-san-francisco-50vz9w20z840) — San Francisco, CA