{"id":3466791,"url":"https://alion.io/job/snotor-senior-data-ingestion-engineer-aws-document-processing-ocr","title":"Senior Data Ingestion Engineer (AWS, Document Processing / OCR)","company":{"id":2122982,"name":"Snotor","domain":"snotor.pro","url":"https://alion.io/company/snotor","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Ukraine"],"countries":["UA"],"hiring_countries":["DE","FR","AT","BE","BG","HR","CY","CZ","DK","FI","HU","IE","IT","NL","PL","RO","ES","SE","EE","GR","LV","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":27,"salary":{"min":2850,"max":4000,"currency":"USD","period":"month","gross":false,"usd_annual":48000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Git","optional":false},{"name":"OCR","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SharePoint","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true},{"name":"Databricks","optional":true}],"status":"live","first_seen_at":"2026-10-05T16:40:53Z","employer_posted_date":null,"last_verified_at":"2026-10-05T16:40:53Z","board_verified":false,"closed_at":null,"days_open":26,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":26},"description":"About the role \n\nWe're hiring two Senior Data Ingestion Engineers for a major client in the insurance sector. You'll design and implement scalable ingestion pipelines for high-volume structured and unstructured insurance documents: PDFs, scans, emails, Word, Excel and PowerPoint files. \n\nThe pipelines feed downstream AI solutions. The work covers OCR and document extraction, text cleaning and normalisation, semantic chunking, metadata tagging, vector storage and RAG preparation, validation, and monitoring. \n\nWhat you'll do \n\nDesign and build scalable document-ingestion pipelines on AWS (S3, Step Functions, CloudWatch). \n\nProcess unstructured documents: PDFs, scanned documents, Word, Excel, PowerPoint and emails. \n\nImplement OCR and document extraction with AWS Textract or equivalent tools, and validate the extraction results. \n\nBuild connectors and integrations with sources such as SharePoint and email. \n\nClean and normalise text, and extract and tag metadata. \n\nPrepare data for RAG: semantic chunking, vector-storage schema design and retrieval. \n\nSet up automated error monitoring, alerting and quality checks. \n\nIntegrate ingestion outputs with downstream AI solutions, following enterprise security and SLA requirements. \n\nMust-have \n\n7+ years of commercial experience as a Data Engineer with Python and SQL. \n\n5+ years of hands-on AWS experience, including S3, Step Functions and CloudWatch. \n\nProven experience building data and document ingestion pipelines in a public cloud. \n\nProcessing of unstructured documents: PDF, scanned documents, Word, Excel, PowerPoint and emails. \n\nOCR and document extraction technologies (AWS Textract or equivalent), including validation of OCR and extraction results. \n\nConnectors and integrations with sources such as SharePoint and email. \n\nText cleaning and normalisation, and metadata extraction and tagging. \n\nAutomated error monitoring for data pipelines. \n\nGit, CI/CD and testing practices. \n\nEnglish at C1 level. \n\nFor every skill above, you should be able to give concrete examples from real projects. \n\nNice to have \n\nVector databases, RAG, semantic chunking, vector-storage schema design and retrieval mechanisms \n\nAWS Textract specifically \n\nAzure and/or Databricks \n\nExperience in insurance or financial services \n\nExperience with enterprise security and low-latency SLA requirements \n\nLocation \n\nFully remote, but you must live in an EU member country and hold a valid residence permit there. \n\nWhat we offer \n\nA 1-year full-time engagement with a major enterprise client \n\nThe option of a direct contract with the client (the details of the cooperation model are discussed individually) \n\nHands-on work at the intersection of document processing, data engineering and GenAI \n\nFully remote work within the EU \n\nHow to apply \n\nPlease send a CV tailored to this role. The client screens CVs strictly and won't review a generic CV or a list of keywords. For each relevant project, please include: \n\nstart and end dates, the context, and your personal role and responsibilities \n\nthe AWS services and tools you used (S3, Step Functions, CloudWatch, Textract and so on) and how you used them \n\nthe document types you processed, how you did the OCR, extraction, cleaning, metadata tagging and validation, and which sources you integrated (SharePoint, email) \n\nany experience with RAG, vector databases, chunking or retrieval, plus your Azure, Databricks and insurance or financial-services experience \n\nPlease also include: \n\nyour expected hourly rate (USD) \n\nyour English level \n\nyears of experience \n\nyour country of residence and residence status \n\nyour citizenship \n\nyour availability date","description_format":"text","description_chars":3656,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"region"},{"name":"France","iso":"FR","kind":"region"},{"name":"Austria","iso":"AT","kind":"region"},{"name":"Belgium","iso":"BE","kind":"region"},{"name":"Bulgaria","iso":"BG","kind":"region"},{"name":"Croatia","iso":"HR","kind":"region"},{"name":"Cyprus","iso":"CY","kind":"region"},{"name":"Czech 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