Data Engineer (Secure Supply Chain/Anti-Counterfeit Platform)
1 day ago
Oxford
Role Overview We are building a high-integrity data platform to support global anti-counterfeit operations, combining physical item fingerprinting (optical labels), cryptography, and supply chain analytics. The Data Engineer will work closely together with Laser and Optics Engineers to design and implement the encryption protocol, database structure, data ingestion pipelines, cloud-based core data infrastructure and analytics engine. This role requires strong experience in cloud-based applications, database design, data pipelines, and data storage architecture. Key Responsibilities • Design and implement a scalable data architecture combining:, • Event and data streaming, • Data lake (object storage, e.g. S3-compatible), • Data warehouse (e.g. Snowflake / BigQuery / Redshift), • Transactional database (SQL or similar), • Define database architecture for item identity, provenance and verification events, • Implement secure data handling practices, including:, • Encryption at rest and in transit, • Field-level encryption for sensitive data, • Integration with KMS / HSM systems for key management, • Integrate with permissioned ledger systems (e.g. Hyperledger Fabric) for provenance anchoring, • Enable analytics use cases by:, • Structuring data for efficient querying and reporting, • Building curated datasets and feature stores, • Support BI tools and dashboards (e.g. Power BI, Looker, Tableau), • Implement data access layers (APIs, views) with role-based controls, • Define and enforce:, • Data validation rules, • Monitoring and alerting for pipeline failures, • Data quality metrics (completeness, consistency, accuracy) Essential Experience • 3–6+ years in data engineering or backend data systems, • Proven experience building data pipelines at scale/streaming systems, • Strong SQL and experience with data modelling (OLTP + OLAP), • Hands-on experience with:, • Distributed data processing, • Data lakes and warehouses, • Strong programming skills (Python or equivalent) for data pipelines, • Knowledge of data formats (Parquet, Avro, JSON), • Understanding of data partitioning, indexing, and performance optimisation, • Experience with API-driven data systems, • Understanding of:, • Encryption (at rest / in transit), • Identity and access management (IAM), • Secure handling of sensitive data, • Awareness of data integrity concepts:, • Hashing, • Digital signatures, • Experience with blockchain / distributed ledger technologies (e.g. Hyperledger), • Exposure to supply chain systems or provenance tracking, • Experience with IoT or hardware-generated data, • Knowledge of privacy-preserving analytics (e.g. differential privacy, federated learning), • Strong analytical thinking and problem-solving, • Ability to work across disciplines (software, hardware, security), • Clear communication of complex technical concepts, • Degree in Computer Science, Engineering, Mathematics, or related field, • (or equivalent practical experience)