GenAI Data Engineer

🔒 Confidential Employer
Posted 7 May 2026
LOCATION
London
TYPE
Contract
LEVEL
Mid-Senior level
CATEGORY
Technology
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

PySpark Python AWS GenAI/LLM RAG SQL Delta Lake ETL

FULL DESCRIPTION

[Employer hidden — sign up to reveal] is hiring a GenAI Data Engineer for a contract role in London.

GenAI Data Engineer

Job details
Posted: 28 April 2026
Location: London
Job type: Contract
Discipline: Technology

Job Description

Your Responsibilities:

  • Design and maintain scalable data pipelines using PySpark, Python, and distributed computing frameworks to support high‑volume data processing.
  • Architect and optimize AWS-based data and AI infrastructure, ensuring secure, performant, and cost‑efficient ingestion, transformation, and storage.
  • Develop, finetune, benchmark, and evaluate GenAI/LLM models, including custom training and inference optimization.
  • Implement and maintain RAG pipelines, vector databases, and document-processing workflows for enterprise GenAI applications.
  • Build reusable frameworks for prompt management, evaluation, and GenAI operations.
  • Collaborate with cross-functional teams to integrate GenAI capabilities into production systems and ensure high-quality data, governance, and operational reliability

Your Profile:

  • Strong experience with PySpark, distributed data processing, and largescale ETL/ELT pipelines.
  • Strong SQL expertise including star/snowflake schema design, indexing strategies, writing optimized queries, and implementing CDC, SCD Type 1/2/3 patterns for reliable data warehousing.
  • Advanced proficiency in Python for data engineering, automation, and ML/GenAI integration.
  • Hands‑on expertise with AWS services (S3, Glue, Lambda, EMR, Bedrock / custom model hosting).
  • Practical experience with GenAI/LLM model creation, finetuning, benchmarking, and evaluation.
  • Solid understanding of RAG architectures, embeddings, vector stores, and LLM evaluation methods.
  • Experience working with structured and unstructured datasets (documents, logs, text, images).
  • Familiarity with scalable data storage solutions (Delta Lake, Parquet, Redshift, DynamoDB).
  • Understanding model optimization techniques (quantization, distillation, inference optimization).
  • Strong capability to debug, tune, and optimize distributed systems and AI pipelines.

Contact

[Employer hidden — sign up to reveal] - Vaishali Srivastava
Email: [Employer hidden — sign up to reveal]
Phone: [contact hidden]

If this position is of interest to you, apply now!

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