Data Engineer (Founding Team)

About this role

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.