Senior Consultant - Data Engineering

Overview

In this Senior Consultant role, you will help build and manage data assets to support pre-deal and post-deal engagements within EY-Parthenon’s Analytics & AI practice. You will shape data pipelines, models, and dashboards, enabling better client decision-making in transactional contexts. You will work with cross-functional teams and directly with clients to deliver practical data solutions and insightful analyses. This is an opportunity to apply analytics to complex, incomplete data and drive tangible business value in a fast-paced environment.

Pay / Benefits

• strong focus on learning and development
• exposure to high-impact deal environments
• collaborative and fast-paced team environment
• opportunity to work with clients across industries

Responsibilities

• Support the project team through the full assignment lifecycle: requirements, data collection, design, development, testing, documentation, implementation, and user training
• Design and build complex database models and dashboards for analysis of large, diverse datasets
• Design analytical solutions (data pipelines, visualisations, machine learning models) and implement proof-of-concepts for client value
• Develop formal deliverables for clients (data dashboards, hosted solutions, reports, presentations)
• Explain technical concepts clearly to clients and help them understand the business impact
• Manage stakeholders' expectations and identify risks, escalating appropriately
• Take ownership of tasks and collaborate across grades and teams

Key requirements

• Approximately 2–5 years’ experience in data engineering, data analytics, or related fields
• Experience with large and complex datasets, Databricks, and distributed systems
• Exposure to transaction support or fast-paced delivery environments beneficial
• Experience building and managing data pipelines and data models
• Strong knowledge of data processing and transformation tools/languages
• Experience with structured and unstructured data sources
• Familiarity with modern data platforms and cloud environments
• Degree in a relevant field or equivalent experience

• Curious and hands-on
• Strong problem-solving and analytical thinking
• Effective communication and stakeholder engagement
• Data pipelines and data models
• Data processing and transformation tools/languages
• SQL