{"id":2138562,"url":"https://alion.io/job/jimmy-technologies-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3904563,"name":"Jimmy Technologies","domain":"jimmytechnologies.com","url":"https://alion.io/company/jimmy-technologies","size_band":"5000+","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":"contractor","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["DE","FR","GB","AT","BE","BG","HR","CZ","DK","FI","HU","IE","IT","NL","NO","PL","RO","ES","SE","CH","EE","GR","IS","LV","LI","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":31,"salary":null,"salary_estimate":{"min_usd":87000,"max_usd":197000,"period":"year","method":"global_role_seniority_cell","sample_n":2127},"experience_years_min":5,"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":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"Unstructured.io","optional":false},{"name":"Azure","optional":true},{"name":"Databricks","optional":true}],"status":"live","first_seen_at":"2026-10-09T00:23:37Z","employer_posted_date":null,"last_verified_at":"2026-10-09T00:23:37Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"We are looking for a Senior Data / Ingestion Engineer for our client, a consultancy that helps banks and insurers transform their operations through AI, automation, and advanced analytics, with a strong focus on Anti-Financial Crime (fraud prevention, AML, KYC) and enterprise AI platforms. You will join their delivery for a Dutch insurance client.\nWe're looking for an engineer with deep experience building robust ingestion pipelines for unstructured documents and integrating OCR and document extraction technologies. You will turn high volumes of insurance documents (PDFs, scans, emails, Office files) into structured, high-quality, AI-ready data that feeds downstream RAG and AI models.\nThis is a long-term remote-first contract position for candidates based in Europe.\nResponsibilities\nDesign and implement scalable pipelines for ingesting high-volume unstructured insurance documents (PDFs, scans, emails, Word, Excel, PowerPoint).\n\nBuild connectors to document sources such as SharePoint and email.\n\nIntegrate, configure, and optimise OCR and document parsing technologies to extract high-accuracy text and layouts.\n\nBuild automated workflows for text cleaning, normalisation, semantic chunking, and metadata tagging.\n\nDesign vector storage schemas and robust retrieval mechanisms (RAG) to feed downstream AI models.\n\nEnsure document processing pipelines meet enterprise security and low-latency SLA requirements.\n\nBuild automated error monitoring and extraction validation loops that flag low-confidence OCR outputs.\n\nApply engineering best practices across the pipeline lifecycle: version control, CI/CD, and testing.\n\nWork Conditions\nStart Date: ASAP\n\nLocation: Remote within Europe (CEE preferred)\n\nLong-term contract-based role: until July 2027 with possible extension\n\nContract with EU LCC\n\nRequirements\n5–10 years' experience in data engineering.\n\nProven experience building data processing and document ingestion pipelines on public cloud platforms.\n\nHands-on experience processing unstructured documents (PDF, Word, Excel, PowerPoint, scans, emails).\n\nExperience building connectors to enterprise sources such as SharePoint and email.\n\nPractical experience with document extraction / OCR tools, e.g. AWS Textract or equivalent.\n\nStrong engineering practices: Git, CI/CD, automated testing.\n\nExperience in banking or insurance is an advantage.\n\nTechnical RequirementsMandatory\nPython, SQL\n\nAWS: S3, Step Functions, CloudWatch\n\nOCR / document extraction: AWS Textract or equivalent\n\nUnstructured document processing and ingestion pipelines\n\nGit, CI/CD, testing\n\nNice to have\nVector databases and RAG architectures\n\nAzure, Databricks\n\nFinancial services / insurance domain experience\n\nHighlightsIf you are passionate about turning unstructured documents into AI-ready data, and want to help leading financial institutions fight financial crime with AI, this role is for you!\nOriginally posted on Himalayas","description_format":"text","description_chars":2921,"description_truncated":false,"requirements":{"experience_years_min":5,"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":"United 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