Data Engineer

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October 22

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MONQ

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B2B • SaaS • Artificial Intelligence

<MONQ> MONQ is an AI-driven negotiation platform that helps enterprise procurement teams optimize negotiation strategies and outcomes for buyers and vendors. Launching Q4 2025, the product provides real-time analytics, automated risk assessment and compliance monitoring, and performance insights designed to reduce costs and accelerate deal cycles for large contracts and global procurement operations.

11 - 50 employees

Founded 2014

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

📋 Description

• 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 • Define, evolve, and manage data schemas for contract intelligence, vendor benchmarking, and negotiation performance analytics • 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 • Build end-to-end monitoring and observability for mission-critical negotiation data pipelines • Collaborate closely with AI, Platform, and Product teams, provisioning datasets, feature tables, and contracts that power autonomous negotiation agents at scale • Create data pipelines that integrate with major procurement systems (SAP, Oracle, Coupa, GEP) and enterprise workflows • Continuously improve efficiency and reliability via comprehensive testing, CI/CD automation, cost/performance tuning for enterprise-scale deployments

🎯 Requirements

• 3+ years building and running data pipelines in AWS or Azure, with experience in enterprise B2B environments and complex data integration challenges • Expert-level programming in Python with focus on production-grade ETL systems; experience with enterprise data at scale • Deep experience with batch and streaming frameworks (Apache Spark, Flink, Kafka Streams, Beam), including orchestration via Airflow, Prefect, or Dagster • Background in legal/procurement document processing, contract analysis, or complex unstructured data parsing (preferred) • Proven track record integrating with major enterprise systems (ERP, procurement platforms, business intelligence tools) (preferred) • Experience building data infrastructure that supports machine learning models and AI agents in production (preferred)

🏖️ Benefits

• 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 • Remote first with quarterly gatherings • Annual team retreat - fully-funded off-site focused on AI innovation and team building • 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