Data Engineer – AWS, AI & Data Transformation / 60-80k P/M

Data Engineer – AWS, AI & Data Transformation / 60-80k P/M

12 month extendable contract

Role Overview

We are looking for an experienced Senior Data Engineer to help build the data foundations required to support AI, analytics and enterprise knowledge initiatives.

This will initially be a strongly hands-on data engineering role, focused on building end-to-end data workflows, transforming structured and unstructured data, and establishing scalable data practices within a complex enterprise environment.

The successful candidate will work closely with Data, AI, Data Science and business teams to identify, extract, transform and prepare data so it can be effectively used for analytics, Generative AI and broader business decision-making.

Over time, the role may evolve towards broader knowledge enablement, helping the organisation transform corporate data into accessible and usable enterprise knowledge.

Key Responsibilities

• Design, build and maintain end-to-end data pipelines and workflows across enterprise data sources.
• Extract, clean, transform and prepare data for use by AI Engineers, Data Scientists, analytics teams and business users.
• Work extensively with both structured and unstructured data, helping define how unstructured information should be captured, governed and made available for AI use cases.
• Build and optimise data transformation processes within an AWS cloud environment.
• Support the development and evolution of enterprise data lakes, lakehouse architectures and data catalogues.
• Write and optimise SQL and Python queries and data processing workflows.
• Partner with AI and Data Science teams to determine when information should be handled through traditional data engineering approaches versus AI / Generative AI solutions.
• Prepare enterprise datasets for machine learning, Generative AI, RAG and other AI-driven applications.
• Automate manual data processes and improve the scalability and reliability of existing data workflows.
• Work with business owners to understand data requirements, identify relevant information sources and translate business problems into practical data solutions.
• Help establish appropriate data governance, metadata, access and data management practices, particularly as the organisation expands its use of unstructured data.
• Help build and maintain internal data cataloguing and data discovery capabilities, including environments where established tools such as Collibra may not yet be in place.
• Navigate a complex organisation and collaborate across Data, Technology, AI, Governance and business teams.
• Help establish a scalable approach for transforming enterprise data into information and knowledge that supports better business decisions.

Required Experience

• Approximately 5–10 years of experience within Data Engineering, Data Platforms or a closely related field.
• Strong hands-on experience building ETL / ELT pipelines and performing complex data transformation.
• Strong practical experience with SQL and Python.
• Experience working with AWS-based data platforms and cloud data architectures.
• Must have experience with technologies such as Amazon Redshift, AWS data services, data lakes and/or lakehouse architectures.
• Experience designing, building or contributing to enterprise data catalogues.
• Good understanding of data governance, metadata management, data quality and data access controls within complex organisations.
• Experience working across large or complex enterprise environments with multiple stakeholders and data owners.
• Strong understanding of structured data, with an interest or experience in solving challenges around unstructured enterprise data.
• Ability to work directly with business stakeholders as well as technical Data, AI and Engineering teams.
• Strong problem-solving skills and the ability to operate where processes, technology and governance frameworks are still being developed.

Highly Desirable

• Previous experience supporting AI, Machine Learning, Data Science or Generative AI initiatives as a Data Engineer.
• Experience preparing and transforming data for LLMs, RAG, semantic search or other Generative AI applications.
• Experience working directly with AI Engineers and Data Scientists to productionise AI use cases.
• Exposure to extracting knowledge from documents, text or other forms of unstructured data.
• Experience establishing data governance approaches in organisations where tooling and standards are still being defined.
• Experience automating data ingestion, transformation, classification or enrichment processes.

Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.