Data Engineer

Oxford Quantum Circuits (OQC)

. Design, build and operate secure data ingestion and transformation pipelines across internal, external and customer data sources .

Posted 9/30/2026full-timeLondon • United KingdomMid-LevelSenior💰 £260,000,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating secure data ingestion and transformation pipelines, with a strong focus on data quality, governance, and machine learning requirements. Proficient in leveraging cloud and on-premise environments to support data infrastructure for advanced analytics and synthetic data generation.

Highest-signal resume keywords

DatabricksSparkDelta LakeSQLData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentMachine Learning Dataset PreparationData Quality ManagementData Lineage TrackingData Security Practices

Soft Skills

Strong Communication SkillsCollaboration Across TeamsOwnership

Tools & Technologies

CI/CD PracticesCloud InfrastructureOn-Premise Data SystemsStreaming Data PipelinesBatch Data Pipelines

Certifications & Qualifications

Degree in Computer SciencePostgraduate Qualification

Industry Keywords

Sensitive DatasetsRegulated DatasetsBanking TransactionsMarket DataQuantum Computing

Tech Stack

Tools & technologies

CloudSparkSQL

About the role

Key responsibilities & impact

Design, build and operate secure data ingestion and transformation pipelines across internal, external and customer data sources
Build data workflows spanning cloud, private-cloud, on-premise and datacentre environments
Develop governed datasets for machine learning and quantum workloads, defining data contracts, versions, quality rules, entitlements, lineage and retention
Create robust training, validation, calibration and untouched test datasets for credible ML evaluation
Transform raw customer data into QPU-permitted features or latent representations and return outputs into governed synthetic datasets
Monitor and optimise pipeline reliability, throughput, latency, storage utilisation and operational cost
Build automated testing and CI/CD practices for data pipelines and infrastructure
Partner across engineering teams to deliver reliable data foundations for customer-facing products
Collaborate across Software, Platform, Security, Machine Learning and Infrastructure teams

Requirements

What you’ll need

Strong hands-on experience with Databricks, Spark, Delta Lake and SQL
Experience building and operating streaming and batch data pipelines
Strong understanding of data quality, lineage, access control and dataset governance
Experience operating data systems across cloud infrastructure and/or private or on-premise environments
Understanding of the specific data requirements associated with ML training, synthetic data and untouched evaluation datasets
Strong understanding of data security, including encryption in transit and at rest, access controls and audit logging
Strong ownership and communication skills, with the ability to collaborate effectively across software, platform, security, ML and infrastructure disciplines
Degree or equivalent practical experience in Computer Science, Software Engineering or a related discipline
Experience working with sensitive or regulated datasets, particularly banking transactions, market data or customer records
Experience supporting data infrastructure used by machine learning workloads
Familiarity with quantum computing or hybrid classical-quantum products
Experience working with data platforms that span cloud and customer-controlled infrastructure
A pragmatic, curious approach and comfort working in a fast-evolving technical environment
A relevant professional or postgraduate qualification

Benefits

Comp & perks

Culture of bold innovation
Opportunity to work with unique lab infrastructure
Opportunity to see your work redefine the limits of computation
World-class team at the forefront of the next computational era