Civic Marketplace
Civic Marketplace
Civic Marketplace स्थानीय सरकारी एजेंसियों के लिए खरीद प्रौद्योगिकी विकसित करता है। इसका मार्केटप्लेस खरीद कार्यालयों को विश्वसनीय और पहले से स्वीकृत विक्रेताओं से अधिक सरलता, पारदर्शिता और कानूनी अनुपालन के साथ सामान और सेवाएँ खरीदने में मदद करता है। इससे पुराने सिस्टम से जुड़ा समय और प्रशासनिक जटिलता कम होती है। कंपनी विविध आपूर्तिकर्ताओं और स्थानीय आर्थिक विकास को भी बढ़ावा देती है तथा सरकारी कार्य, लॉजिस्टिक्स और परामर्श के अनुभव को जोड़कर सार्वजनिक क्षेत्र की खरीद व्यवस्था को बेहतर बनाने में योगदान देती है।

Data Engineer (Mid-Senior, Remote UK)

Own the data foundation behind Civic Marketplace’s government procurement platform, from entity resolution and canonical models to reliable ingestion and AI-ready retrieval. This role leads data quality, provenance, and vector pipeline work as the company’s first dedicated data engineering hire.

विवरण

  • Own a reliable canonical procurement dataset that supports analytics and agentic procurement
  • Investigate and resolve quality problems spanning suppliers, agencies, solicitations, contracts, and awarded quotes
  • Build observable, dependable, and cost-conscious ingestion pipelines for APIs, files, scraped content, PDFs, and other external sources
  • Match supplier records across legal entities, alternate spellings, trading names, subsidiaries, registries, and identifiers
  • Establish shared canonical models for suppliers, contracts, commodities, and agencies
  • Implement testing, lineage, freshness, provenance, and self-service data tooling
  • Plan ingestion and storage for agentic workflows and improve vector systems such as Pinecone for RAG
  • Partner with the Head of Engineering on data and platform architecture
  • Develop pipelines, participate in pager coverage, and trace faulty data back to its source
  • Work with product engineering, customer success, and the Growth Lead
  • Act as Civic Marketplace’s first dedicated data engineer and lead the function with the Head of Engineering

आवश्यकताएँ

  • Experience building data platforms in a startup or scale-up environment rather than maintaining an inherited system
  • Advanced SQL and Python skills, with the judgement to choose alternatives when a warehouse is not the right solution
  • Evidence of designing a data model used by others, including a clear understanding of what you would revise
  • Hands-on work with unreliable external inputs such as undocumented APIs, file drops, scraped pages, PDFs, and data outside your control
  • Experience with entity resolution or record linkage, or demonstrated aptitude for solving those problems
  • Commercial judgement to prioritize data issues that affect revenue over merely interesting defects
  • A diagnostic approach that identifies why a metric is wrong before implementing a correction
  • A systems mindset focused on scalable data infrastructure instead of one-off pipelines
  • Strong practical fluency with AI technologies
  • Resilience and a constructive outlook in a fast-changing startup
  • Ability to work independently and remotely across timezones with limited supervision
  • Interest in public-sector data
  • Experience in govtech, public-sector technology, civic tech, public records, or open data is advantageous
  • Knowledge of supplier and procurement data, including SAM.gov, UEI, DUNS, NAICS, UNSPSC, cooperative purchasing, COG, or NIGP is advantageous
  • Experience with OpenSearch, Elasticsearch, or vector systems such as Pinecone or Milvus supporting an LLM product is advantageous
  • Bilingual English and Spanish communication skills are especially valuable
  • Experience as the first data hire is advantageous

लाभ

  • Competitive compensation with early-stage equity
  • Comprehensive medical, dental, and vision coverage
  • Flexible paid time off
  • Remote-first work with meaningful timezone flexibility
  • Access to a broad AI tooling suite, including Claude Pro, HubSpot, Make, and Notion
  • Regular team offsites, including international gatherings
  • Direct collaboration with the founders and close involvement in building the company

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