Consultant – Manager, Data Management, AI & Data, Engineering & Transformation

Overview

In this role you will lead and deliver data management initiatives for clients, shaping robust governance, quality, migration and metadata approaches. You’ll work with cross-functional teams on next-gen data platforms and analytics projects, helping clients modernise and scale their data capabilities. You join a collaborative, growth-focused AI & Data team that values training and real impact. This is a client-facing, multi-disciplinary role in a leading professional services firm.

Pay / Benefits

• hybrid working in London
• training and development opportunities
• collaborative culture
• wellbeing focus
• opportunities to work with leading clients
• supportive, inclusive environment

Responsibilities

• Collaborate with client and internal teams to translate business needs into data management strategies
• Design, implement and optimise Data Quality frameworks and tools
• Oversee complex Data Migration projects from strategy to post-migration validation
• Develop Metadata Management strategies including data cataloguing and data lineage
• Lead Master Data Management (MDM) initiatives with governance and data models
• Build scalable data pipelines, datasets and models for analytics and operation
• Stay updated on data management advances and technologies; drive scalable, compliant data solutions
• Manage deliverables and client relationships within agile delivery environments

Key requirements

• Hands-on experience in delivering data management solutions
• Experience designing and managing Data Quality programs
• Experience executing Data Migration projects with mapping and validation
• Experience with Metadata Management practices (cataloguing, lineage, glossaries)
• Experience implementing MDM solutions with governance and synchronization
• Agile delivery experience
• Strong analytical and problem-solving skills
• Programming skills in SQL, Python or similar
• Data Engineering experience with SQL, big data tools (Spark, Hadoop) and ETL/ELT
• Knowledge of data governance, security and privacy across data lifecycle
• Familiarity with cloud data services (AWS, Azure, GCP) and data modelling techniques

• Analytical mindset
• Team collaboration
• Attention to detail
• SQL
• Python
• Spark

…