AI Data Engineering Lead

Ideagen

AI Data Engineering Lead at Ideagen, focusing on data quality and governance for AI models in regulated industries. Leading a team, shaping data architecture, and ensuring compliance.

Posted 4/30/2026full-timeRemote • 🇬🇧 United KingdomSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

Leading and developing a team of AI data engineers, setting clear technical standards, supporting career growth, and scaling the function as the programme grows
Defining the technical direction for AI data engineering, including architecture decisions, tooling choices, and delivery practices across the organisation
Designing and building the end‑to‑end AI data platform, from operational product data and regulatory sources through cloud storage and transformation pipelines to training‑ready datasets
Owning dataset versioning and lineage so every training artefact is traceable, reproducible, and auditable across the full model lifecycle
Building and maintaining large‑scale regulatory and operational corpora in collaboration with domain experts, ensuring data quality and consistency
Architecting and operating AWS‑based data infrastructure at production scale with a focus on reliability, security, and performance
Defining and enforcing data governance standards, including quality checks, labelling conventions, and data handling frameworks
Leading GDPR compliance for AI training data in partnership with Legal and ensuring best practice is embedded from the start

Requirements

What you’ll need

You are a senior data engineer or technical lead with prior experience leading teams and owning large data platforms end to end
You have deep production experience with Python and SQL and write data transformation code that is robust, readable, and reusable
You have designed and run AWS data stacks at scale, including services such as S3, Glue, Athena, Kinesis, Lambda, and IAM
You understand ML training data pipelines and know how they differ from analytics workloads, including dataset formats, splits, and quality constraints
You bring strong data governance instincts and design for versioning, lineage, and auditability from day one
You are comfortable working with legal and compliance partners on sensitive data handling and regulatory requirements
You communicate clearly across disciplines and work effectively with AI engineers, product leaders, and domain specialists
Experience with NLP or LLM training data, data version control tools, or regulated industry software is valuable but not essential.

Benefits

Comp & perks

Benefits at Ideagen

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonSQLdata transformationdata governancedataset versioningdata lineageML training data pipelinesNLPLLM training datadata quality

Soft Skills

leadershipcommunicationcollaborationproblem-solvingorganizational skillscareer development supporttechnical direction settingcross-disciplinary communicationteam managementstakeholder engagement