Skiffra is building the intelligence layer for the physical world. We translate complex, real-world environments into clear, actionable data.
While most AI companies focus on digital industries, we design AI native orchestration systems for the sectors that extract, move, and build ecosystems around us. We turn messy, high stakes operations into intelligent, adaptive workflows that improve decisions in real time.
Our first proving ground is mining and natural resources, but the platform is modular by design and built to scale into any industry where decisions are expensive and the consequences are real.
As the Data Engineer, you will build the circulatory system of Skiffra’s AI-native orchestration platform. This is a hands-on, high-autonomy role where you’ll bridge the gap between messy enterprise reality and clean AI reasoning. You won’t just move data; you will architect the foundation that allows autonomous agents to understand and act on complex industrial systems. You’ll work directly with the founding team to ship zero-to-one systems where reliability isn't a goal, it’s the baseline.
What You’ll DoDesign and maintain a robust semantic layer that translates raw database schemas into high-context metadata, allowing LLMs and autonomous agents to reason across enterprise data
Integrate ERPs, operational tools, and legacy systems into a clean, unified internal data layer that powers Skiffra’s orchestration engine
Design the schemas and data contracts consumed by LLMs and workflow engines to ensure predictable, high-fidelity inputs from varied, often "messy" sources
Ensure every data point carries the necessary lineage and metadata for an LLM to understand its business significance
Architect the end-to-end ingestion and normalization pipelines for structured, semi-structured, and unstructured data, transforming fragmented enterprise fragments into a high-fidelity stream for AI agents
Implement the monitoring, observability, and automated data quality gates necessary to ensure our orchestration engine doesn't act on stale or corrupted enterprise context
Partner closely with product and engineering to translate complex operational needs into scalable data systems
Operate with speed and rigor in environments where reliability matters
7+ years building production-grade data engineering or backend systems
Strong Python and SQL mastery
Experience with ETL/ELT pipelines and API-based integrations
Experience with cloud data infrastructure and streaming or event-driven systems
Ability to work independently and make sound technical tradeoffs
Proven track record building systems where data discovery and cataloging were core features
Ability to make sound technical tradeoffs and thrive in "zero-to-one" environments without a roadmap or perfect documentation
Experience with industrial, operational, or enterprise data systems
Experience designing data contracts or vector stores specifically consumed by LLMs, RAG systems, or autonomous agents
Experience managing data access controls and identity within data pipelines
Startup or founding-team experience
We value speed, clarity, and technical rigor. We favor simple systems over clever ones, prototypes over over-planning, and ownership over handoffs. You’ll work directly with founders and ship things that matter quickly.
Location & Work ModelThis is a hybrid role with regular in-person collaboration in Los Angeles or the San Francisco Bay Area. We are not a remote-only company.
Work AuthorizationCandidates must be authorized to work in the United States. We are not able to offer visa sponsorship for this role.
Benefits & EligibilityThis position is eligible for Skiffra’s standard benefits, including health insurance and retirement plans, and may also qualify for participation in the Company’s bonus and incentive programs.
Equal OpportunitySkiffra is an equal opportunity employer. We value diversity and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic.
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