Data Engineer

At OQC, we aren't just theorising about the future; we're building it. Born from a philosophy of bold innovation, we've successfully transitioned quantum computing from an academic dream into a commercial reality. We've recently closed our £260 million Series C funding round.

• 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
• Transform raw customer data into QPU-permitted features or latent representations
• Monitor and optimise pipeline reliability, throughput, latency, storage utilisation and operational cost
• Build automated testing and CI/CD practices for data pipelines and infrastructure

• 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 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
• Degree or equivalent practical experience in Computer Science, Software Engineering or a related discipline
• Nice-to-have: experience with sensitive or regulated datasets (banking transactions, market data or customer records)
• Nice-to-have: familiarity with quantum computing or hybrid classical-quantum products

• Based in London, hybrid
• Work with unique lab infrastructure