AI Data Engineer

About the Role My client is looking for a hands-on AI Data Engineer to design, build and optimise scalable data infrastructure and pipelines that power advanced AI and analytics initiatives. You will work closely with Software Engineering and AI/ML teams to ensure high-quality, reliable and accessible data across structured and unstructured datasets. Key Responsibilities: Design, develop and maintain robust ETL/ELT data pipelines across multiple data sources. Build and optimise scalable data workflows using technologies such as Airflow, dbt or equivalent orchestration tools . Process and transform complex structured and unstructured datasets. Develop data solutions that support AI, ML and advanced analytics use cases . Implement data validation, testing, monitoring and quality frameworks. Diagnose data issues and proactively improve pipeline reliability and performance. Collaborate with AI/ML and Software Engineers to provide reliable and accessible data. Apply best practices around data governance, security, quality and lineage . Document data architectures, metadata and data flows to ensure transparency and reproducibility. Optimise data pipelines and infrastructure for scalability, performance and cost efficiency. Requirements: 5+ years of experience in Data Engineering, ETL development or Data Warehousing. Strong hands-on experience with Python and SQL . Experience with Airflow, dbt, Luigi or similar workflow orchestration technologies . Strong understanding of big data architectures and scalable data pipelines . Experience working with large-scale structured and unstructured datasets. Hands-on experience with at least one major cloud platform: Azure, AWS or GCP . Strong understanding of data quality, validation, monitoring and governance. Experience diagnosing complex data and pipeline issues. Strong communication skills with the ability to work with both technical and non-technical stakeholders. Bachelor s degree in Computer Science, Engineering or a related technical discipline . Ideal Candidate The ideal candidate will be a production-focused Data Engineer rather than a BI or analytics specialist, with a strong engineering mindset and experience building data platforms that support modern AI/ML environments . Experience with Spark, data lakes/lakehouses, streaming, vector databases, RAG pipelines or AI data platforms would be highly advantageous. Salt is acting as an Employment Agency in relation to this vacancy.

Desired Candidate Profile

Requirements: 5+ years of experience in Data Engineering, ETL development or Data Warehousing. Strong hands-on experience with Python and SQL . Experience with Airflow, dbt, Luigi or similar workflow orchestration technologies . Strong understanding of big data architectures and scalable data pipelines . Experience working with large-scale structured and unstructured datasets. Hands-on experience with at least one major cloud platform: Azure, AWS or GCP . Strong understanding of data quality, validation, monitoring and governance. Experience diagnosing complex data and pipeline issues. Strong communication skills with the ability to work with both technical and non-technical stakeholders. Bachelor s degree in Computer Science, Engineering or a related technical discipline . Ideal Candidate The ideal candidate will be a production-focused Data Engineer rather than a BI or analytics specialist, with a strong engineering mindset and experience building data platforms that support modern AI/ML environments . Experience with Spark, data lakes/lakehouses, streaming, vector databases, RAG pipelines or AI data platforms would be highly advantageous.