Maidenhead, United Kingdom | Posted on 20/03/2026
VE3 is a technology and business consultancyfocused on delivering end-to-end technology solutions and products. We havesuccessfully serviced enterprises across multiple markets, including the publicand private sectors. Our services span all aspects of business, providing aholistic approach to managing an organization. We are committed to providingtechnical innovations and tools that empower organizations with criticalinformation to facilitate decision-making that results in businesstransformation through cost savings and increased operational efficiency. Ourcommitment to quality is adopted throughout the organization and sets thefoundation for delivering our full suite of capabilities.
Job Description
Role Summary VE3’s Data Engineer will design, build, and optimise the data pipelines, models, and structures that support high-quality, interoperable, and AI-ready services. The role will ensure that data is consistently ingested, transformed, validated, enriched, and exposed in a way that supports reliable API performance, improved discoverability, and future analytics or AI use cases. The Data Engineer will also support metadata quality, data modelling, and operational data management.
Requirements
Key Responsibilities
Design and develop scalable data pipelines and transformation processes for structured and semi-structured datasets.
Build and maintain data models, schemas, mappings, and metadata structures that support API and search use cases.
Implement data validation, profiling, reconciliation, and quality controls across ingestion and publishing workflows.
Support the preparation of clean, consistent, and machine-readable datasets for operational and AI-enabled services.
Work closely with API developers and AI engineers to expose data efficiently and accurately through services and search layers.
Optimise data storage, query performance, and interoperability across source and target systems.
Contribute to lineage, cataloguing, documentation, and governance of data assets.
Support troubleshooting, defect resolution, and continuous improvement of data processes.
Maintain technical documentation and support knowledge transfer into live service support models.
Skills & Experience
Strong experience in data engineering, ETL/ELT, and data modelling.
Experience with SQL and data processing tools/frameworks such as Python, Spark, Databricks, or equivalent.
Experience working with relational, document, and cloud-native data platforms.
Understanding of metadata standards, data quality management, schema evolution, and interoperability.
Ability to design data structures that support both transactional services and downstream AI/search use cases.
Experience with version control, automation, and engineering best practices.
Experience with semantic metadata, search indexing, vector-ready data preparation, or API-linked data services.
Familiarity with data catalogues, lineage tooling, and governed data-sharing models.
Experience supporting cloud-based and production-grade data services.
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