Senior Data Engineer — Document & AI Pipelines
About the company
Tracium builds AI-assisted technical documentation software that turns complex manuals and engineering documents into structured, traceable information. Starting with maritime, we help technical teams extract maintenance information and create documentation through document intelligence and S1000D authoring.
Your tasks
You will build the data foundation connecting source documents, AI processing, human review, and downstream systems. Your focus will be reliable processing, clear data models, and traceability throughout the document lifecycle.
- Design document ingestion and processing pipelines for PDFs, XML, and related technical data.
- Build workflows for parsing, enrichment, validation, indexing, and export.
- Define data models for document structure, extracted entities, maintenance tasks, and source references.
- Implement document versioning, processing history, and reproducible reprocessing.
- Make pipelines resilient through retries, monitoring, automated checks, and clear failure handling.
- Work with AI engineers to productionise extraction and retrieval workflows.
- Support integrations with authoring tools, customer APIs, and ERP systems.
Requirements
- Experience designing and operating production data pipelines.
- Strong Python, SQL, and data modelling skills.
- Experience with workflow orchestration, asynchronous processing, and object storage.
- A practical approach to testing, observability, and data quality.
- Experience with cloud infrastructure, containers, and infrastructure as code.
- The ability to take ownership from initial design through production support.
- Clear communication in English.
- Document processing, XML.
- Search indexes, vector databases, or AI data pipelines.
- Multi-tenant platforms and private deployment environments.
What we offer
Own the data architecture of a growing product and help make complex technical information dependable, searchable, and usable.
How to apply
Send your CV or professional profile and a brief description of a pipeline or data platform you have built, including your contribution and the challenges you solved.