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About the Role
We are looking for a highly autonomous engineer to take technical ownership of an early-stage art valuation platform. You will work closely with a non-technical founder and domain experts while supporting a small, distributed UX, data, and machine-learning team.
Responsibilities
- Own and develop a Python-based data platform that discovers, captures, normalizes, and processes records from more than 30 web, API, and bulk-data sources.
- Design reliable pipelines for information extraction, entity resolution, assertion reconciliation, and end-to-end lineage, using a combination of deterministic methods and batch LLM processing.
- Build projections of canonical data for machine-learning datasets, website content, tabular outputs, and connection graphs; progressively introduce orchestration and operational monitoring.
- Own the company’s technical infrastructure, including GCP, Terraform, IAM, Google Groups, Firebase, and the evolution toward a dedicated application backend.
- Support product delivery through backend integrations and occasional frontend work, while helping the ML team shape technical approaches, priorities, and roadmaps.
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Requirements
- Strong Python engineering experience, including the design of maintainable data pipelines and production data-processing systems.
- Experience integrating heterogeneous external data sources, such as web pages, APIs, object storage, and bulk datasets, with appropriate retrying, validation, observability, and scheduling.
- Practical cloud and infrastructure experience, ideally with GCP, infrastructure as code, IAM, and secure access management.
- Backend development experience and sound judgment around APIs, data models, system architecture, and the transition from prototypes to production systems.
- Ability to operate independently in an early-stage environment, communicate clearly with technical and non-technical colleagues, and balance short-term delivery with long-term architecture.
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Nice to Have
- Experience with Dagster or another data orchestrator, Firebase, FastAPI, Terraform, and GCP services.
- Familiarity with LLM-based extraction pipelines, Gemini batch processing, entity resolution, knowledge graphs, or data provenance systems.
- Experience supporting machine-learning teams and preparing training, evaluation, or feature datasets.
- Web scraping experience, particularly across sources with different update frequencies and levels of complexity.
- Interest in art, auctions, provenance, valuation, or other data-rich specialist domains.
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