About Monq
Monq is building the first AI platform specifically designed for strategic procurement negotiation. We're creating a blue ocean in a $4.2 trillion market that has been ignored by existing AI solutions. Our team brings together deep technical expertise in AI with proven experience in enterprise software and procurement. We're backed by forward-thinking investors who understand the massive opportunity in applying advanced AI to high-value B2B negotiations. We are founded and backed by Revolut and HSBC executives.
About the Role
Data Engineers are the backbone of Monq. They design, build, and maintain the scalable data infrastructure that powers our autonomous negotiation agents. You'll work closely with AI engineers, product teams, and procurement domain experts to transform complex contract data, vendor information, and negotiation histories into structured, reliable insights that drive intelligent decision-making across our platform.
What You Will Do
Build Enterprise Contract Data Infrastructure: * Design and operate performant, scalable ingestion pipelines processing high-volume contract data, vendor databases, and procurement system integrations from Fortune 500 enterprises * Create sophisticated data parsing systems for complex legal/procurement documents, multi-dimensional deal terms, and procurement workflow data * Build real-time data feeds supporting autonomous negotiation agents and strategic decision-making dashboards
Manage Strategic Procurement Data Architecture: * Define, evolve, and manage data schemas for contract intelligence, vendor benchmarking, and negotiation performance analytics—from raw contract staging to high-quality feature stores for AI agents * Build comprehensive contract data catalogues ensuring discoverability and lineage tracking for complex procurement datasets * Design data models that support multi-dimensional optimisation across price, terms, risk, timeline, and relationship factors
Ensure Enterprise-Grade Data Operations: * Build end-to-end monitoring and observability for mission-critical negotiation data pipelines: owning data quality, latency, completeness, and lineage for $1M+ contract processes * Champion secure, governed data practices for sensitive enterprise contract information: advanced access controls, secrets management, encrypted data-in-transit/at-rest, and compliance with enterprise security frameworks * Implement robust audit trails and data governance for high-stakes negotiation processes
Enable AI-Powered Negotiation: * Collaborate closely with AI, Platform, and Product teams, provisioning datasets, feature tables, and contracts that power autonomous negotiation agents at scale * Build data infrastructure supporting real-time contract analysis, vendor research automation, and strategic negotiation planning * Create data pipelines that integrate with major procurement systems (SAP, Oracle, Coupa, GEP) and enterprise workflows
Drive Operational Excellence: * Continuously improve efficiency and reliability via comprehensive testing, CI/CD automation, cost/performance tuning for enterprise-scale deployments * Lead incident response and root-cause analysis for data systems supporting critical procurement negotiations * Optimise data infrastructure costs while maintaining enterprise-grade performance and reliability standards
Competitive Package:
- Competitive compensation
- Significant equity stake - play a real part in Monq's potential to capture a $4.2T market
- Bi-annual performance bonuses tied to successful pilot deployments and customer outcomes
Work Environment:
- Remote first with quarterly gatherings
- Direct collaboration with Fortune 500 procurement teams
- Annual team retreat - fully-funded off-site focused on AI innovation and team building
Career Growth:
- Visa sponsorship is available for exceptional candidates who complete our recruitment process
- Opportunity to define the future of AI-powered enterprise negotiations
- Direct mentorship from experienced AI researchers and enterprise software veterans
Others:
- No HR organisation
- Minimum 30 days of annual leave and a day off in the month of your birthday
- Flexible working hours as long as we get the things done
- Temporary work from abroad up to 120 days a year (certain limitations apply depending on your nationality/work authorisation status and tax obligations)
Essential Qualifications:
- Enterprise Data Engineering Expertise: 3+ years building and running data pipelines in AWS or Azure, with experience in enterprise B2B environments and complex data integration challenges
- Advanced Technical Skills: Expert-level programming in Python with focus on production-grade ETL systems; experience with enterprise data at scale
- Modern Data Pipeline Mastery: Deep experience with batch and streaming frameworks (Apache Spark, Flink, Kafka Streams, Beam), including orchestration via Airflow, Prefect, or Dagster
Preferred Qualifications:
- Contract/Document Processing Experience: Background in legal/procurement document processing, contract analysis, or complex unstructured data parsing
- Enterprise Integration Experience: Proven track record integrating with major enterprise systems (ERP, procurement platforms, business intelligence tools)
- AI/ML Pipeline Experience: Experience building data infrastructure that supports machine learning models and AI agents in production
Technical Requirements:
- Data Modelling & Schema Management: Demonstrated expertise designing and evolving schemas for complex enterprise data, including data contracts and comprehensive cataloguing systems
- API & Enterprise Integration: Advanced skills building data ingestion from REST/gRPC APIs, enterprise file systems, message queues (SQS, Kafka), and complex SaaS integrations with robust error handling
- Storage & Query Engines: Strong expertise with RDBMS (PostgreSQL, MySQL), NoSQL systems (DynamoDB, Cassandra), data lakes (Parquet, ORC), and modern warehouse architectures
- Enterprise Security & Compliance: Deep understanding of data encryption, secrets management, RBAC/ABAC, and compliance frameworks relevant to enterprise procurement data
- DevOps & Automation: Expert-level comfort with CI/CD for data systems, infrastructure as code (Terraform), version control, and enterprise deployment workflows
Essential Skills:
- Observability & Quality: Deep familiarity with metrics, logging, tracing, and data quality tools (Great Expectations, Monte Carlo, custom validation suites) for mission-critical systems
- Collaborative Leadership: Experience working closely with AI engineering, platform, and business teams in fast-paced, high-stakes environments
- Enterprise Mindset: Understanding of enterprise software requirements including security, scalability, audit compliance, and integration complexity
- Problem-Solving: Ability to architect solutions for complex, multi-dimensional data challenges in enterprise procurement environments
