Data Engineer

Monq
Greater London, UK
7 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
£120,000.0 - £130,000.0
Working hours
Regular working hours

Tech stack

3d Models Application Programming Interfaces (APIs) Artificial Intelligence Airflow Amazon Web Services Microsoft Azure Software as a Service Continuous Integration Data Architecture Data Governance Data Infrastructure Extract Transform Load (ETL)
+28 more
Data Systems Data Warehousing Relational Databases Python (Programming Language) NoSQL Oracle (Applications) Performance Tuning Queueing Systems Role-Based Access Control DataOps SAP (Applications) Data Streaming Systems Integration Unstructured Data Data Logging Enterprise Software Applications Data Ingestion Delivery Pipeline Apache Spark Data Lakes Apache Flink Real Time Data Apache Kafka Coupa Procurement Amazon Simple Queue Service (SQS) Terraform Grpc Data Pipelines

Job description

Data Engineers are the backbone of Monq, building the scalable data infrastructure powering our autonomous negotiation agents. You’ll work with AI engineers, product teams, and procurement experts to turn complex contract data, vendor information, and negotiation histories into reliable insights. We are building the data foundation for AI agents to parse deal terms, benchmark conditions, and optimise outcomes in high-stakes enterprise environments., * Design scalable ingestion pipelines for high-volume contract data, vendor systems, and procurement integrations

  • Create advanced parsing for legal/procurement documents and multi-dimensional deal terms
  • Build real-time data feeds for negotiation agents and decision dashboards

Manage Strategic Procurement Data Architecture

  • Define and evolve schemas for contract intelligence, vendor benchmarking, and negotiation analytics
  • Build comprehensive data catalogues with discoverability and lineage
  • Design models supporting optimisation across price, terms, risk, timeline, and relationship factors

Ensure Enterprise-Grade Data Operations

  • Own data quality, latency, completeness, and lineage for mission-critical pipelines
  • Champion secure, governed practices for sensitive contract data
  • Implement audit trails and compliance for high-stakes negotiations

Enable AI-Powered Negotiation

  • Work with AI, Platform, and Product teams to provision datasets and features for negotiation agents
  • Build infrastructure for real-time contract analysis and vendor research automation
  • Create pipelines integrating with SAP, Oracle, Coupa, GEP, and enterprise workflows

Drive Operational Excellence

  • Improve efficiency through testing, CI/CD, and cost/performance tuning
  • Lead incident response and root-cause analysis
  • Optimise infrastructure cost while maintaining enterprise-grade reliability

Requirements

  • 3+ years building enterprise-scale data pipelines in AWS or Azure
  • Expert Python for production ETL
  • Strong experience with batch/streaming frameworks (Spark, Flink, Kafka Streams, Beam) and orchestrators (Airflow, Prefect, Dagster)

Preferred Qualifications

  • Experience in contract/legal document processing or complex unstructured data
  • Integration experience with enterprise systems (ERP, procurement, BI)
  • Experience supporting ML/AI models in production

Technical Requirements

  • Strong data modelling and schema design for enterprise datasets
  • Advanced API ingestion (REST/gRPC), message queues (SQS, Kafka), SaaS integrations
  • Expertise with RDBMS, NoSQL, data lakes, and warehouse architectures
  • Deep knowledge of security, encryption, RBAC/ABAC, compliance
  • CI/CD for data systems, IaC (Terraform), and enterprise deployment workflows

Essential Skills

  • Observability, metrics, logging, tracing, data quality frameworks
  • Ability to collaborate with AI, platform, and business teams
  • Understanding enterprise security, scalability, audit, and integration needs
  • Strong problem-solving for multi-dimensional data challenges

Benefits & conditions

Competitive Package

  • UK salary: £120,000-£130,000 (transparent, finalised post-process)
  • Significant equity stake
  • Bi-annual performance bonuses tied to customer outcomes

Work Environment

  • Remote-first with quarterly gatherings
  • Direct collaboration with Fortune 500 procurement teams
  • Fully-funded annual AI innovation retreat

Career Growth

  • Visa sponsorship for exceptional candidates
  • Define the future of AI-powered enterprise negotiations
  • Mentorship from senior AI and enterprise software leaders

Other Benefits

  • No HR organisation
  • Minimum 30 days annual leave + birthday day off
  • Flexible hours
  • Temporary work abroad up to 120 days/year (subject to nationality/tax rules)

Interview Process

Initial Screening (30 min, only if needed)

  • Review background and motivation
  • Overview of Monq’s data challenges
  • Alignment on goals and expectations

Online Assessment (45 min)

  • Technical data engineering and cultural fit

Technical Architecture Interview (60 min)

  • Real-world pipeline design for contract processing
  • System design for enterprise integrations
  • Scalability, security, reliability discussion

Problem-Solving Interview (45 min)

  • Deep dive into a complex data challenge

Bar Raiser & On-site Collaboration (half-day)

  • Discussion with co-founder
  • Work with data/AI teams on current pipeline issues
  • Meet procurement/domain experts and enterprise stakeholders

About Monq

Monq is building the first AI platform for strategic procurement negotiation, creating a blue ocean in a $4.2T market overlooked by AI. Our team combines deep AI expertise with enterprise software and procurement experience. Backed by forward-thinking investors and leaders from Revolut and HSBC, we’re positioned to become the category-defining platform for AI-powered procurement.

Every 1% improvement in strategic procurement represents a $42B market impact. We’re not just building software-we’re creating the future of how enterprises negotiate their most critical deals.

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