AI Data Engineer (DV) – ML, ETL & Data Modeling

Accenture PLC; Greater London; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

25 days vacation per year

Private medical insurance

3 extra days leave per year for charit

Job summary

Accenture is seeking a Data Engineer with AI knowledge at Associate Manager level. Location options include London, Manchester, Birmingham or Bristol, with travel to client sites across the UK. A DV clearance is required to be eligible.

The role emphasizes deploying ML models, building robust ETL pipelines, and contributing to data architecture and analytics. The successful candidate will engage in agile delivery, collaborate with cross-functional teams, and stay current with generative AI

Qualifications

• Strong proficiency in Python.
• Extensive experience with cloud platforms (AWS, GCP, or Azure).
• Experience with data warehousing and lake architectures.
• ETL/ELT pipeline development.
• SQL and NoSQL databases.
• Distributed computing frameworks (Spark, Kinesis etc).
• CI/CD, TDD and version control best practices.

Responsibilities

• Deploy machine learning models to production and monitor their performance.
• Implement ETL pipelines and orchestrate data flows.
• Define, document and iterate data mappings based on data modelling concepts.
• Re‑engineer data pipelines to be scalable and repeatable.
• Navigate, explore and query large scale datasets.
• Build data transformation processes and metadata management.
• Identify and resolve data quality issues.

Skills

Python

Cloud platforms

Data warehousing

ETL/ELT

SQL/NoSQL

Distributed computing

CI/CD

Docker/Kubernetes

Infrastructure as Code

AI/ML projects

Tools

Docker

Kubernetes

Terraform

CloudFormation

Spark

Kinesis

Job description

Accenture is seeking a Data Engineer with AI knowledge at Associate Manager level. Location options include London, Manchester, Birmingham or Bristol, with travel to client sites across the UK. A DV clearance is required to be eligible.

The role emphasizes deploying ML models, building robust ETL pipelines, and contributing to data architecture and analytics. The successful candidate will engage in agile delivery, collaborate with cross-functional teams, and stay current with generative AI