Senior Consultant - Data Engineering (Analytics & AI)

Location: London, UK (or flexible)

Service Line: Strategy and Transactions

Firm: EY-Parthenon

Role Overview

EY-Parthenon is looking for a motivated Senior Consultant to join its Analytics & AI practice, with a focus on Data Engineering. This role is ideal for someone with a strong commercial and technical foundation as well as a curious, problem-solving mindset, who is passionate about working with data to support pre-deal and post-deal engagements. You will play a key role in building, shaping, and managing data assets where data is often incomplete, complex, and fragmented. You will work closely with client teams to prepare, structure, and transform data, enabling better decision-making during transactions and helping clients unlock value.

Key Responsibilities

• Support the project team in day-to-day activities throughout the life-cycle of an assignment – requirements definition, specification, data collection, solution design, development, testing, documentation, implementation, and user training.
• Design and build complex database models and insightful visualisation dashboards to perform analysis on large diverse datasets.
• Work independently or with a team in designing analytical solutions (data pipelines, visualisations, machine learning models), undertaking proof-of-concepts, and implementing these solutions to help clients to compete effectively in this dynamic environment with the support of Directors and Partners.
• Work directly with clients as well as other EY specialist teams to develop formal deliverables for clients including data dashboards (Excel or other data visualisation tools), web-hosted solutions, Word reports, and PowerPoint presentations.
• Explain complex technical concepts underpinning your analysis in simple terms to clients to help them understand how their business needs are being addressed.
• Manage stakeholders’ expectations in relation to deliverables.
• Identify risk on the assignment, involving Engagement Manager/Director/Partner appropriately in its resolution.
• Take ownership of your tasks and work collaboratively with members of different grades within and across teams.

Core Experience

• Approximately 2-5 years’ experience in data engineering, data analytics, or related fields, ideally in a consulting or in-house strategy environment.
• Experience working with large and complex datasets, ideally in structured databases and distributed systems like Databricks.
• Exposure to transaction support or fast-paced delivery environments is beneficial.

Technical Skills

• Experience in building and managing data pipelines and data models.
• Strong working knowledge of data processing and transformation tools and languages.
• Experience working with structured and unstructured data sources.
• Familiarity with modern data platforms and cloud environments is advantageous.

Mindset & Approach

• Are curious and hands-on, with a strong desire to explore and understand data.
• Enjoy working with messy, imperfect datasets and finding ways to make them usable.
• Are comfortable learning new tools and approaches quickly, based on what the situation requires.
• Thrive in fast-paced, deal-driven environments, where priorities can shift quickly.
• Take ownership and show initiative in solving problems.
• Are motivated by delivering practical outcomes, not just technical outputs.

Consulting & Communication Skills

• Ability to explain technical concepts in a clear, structured way.
• Strong problem-solving and analytical thinking skills.
• Willingness to engage with stakeholders and understand business context.

Qualifications

• Degree in a relevant field (e.g. Computer Science, Economics, Mathematics, or similar) or equivalent experience.

Key Attributes

• Ability to work with clients and model users, identify their particular use case requirements, design appropriate solutions to load data, perform complex calculations, derive corollaries and deliver interface tools to provide repeatable visual output.
• Strong business acumen and technical knowledge to translate commercial problem into data requirement and formulate analytics solution.
• Strong oral and written communication skills – including experience of writing reports, drafting presentations and developing data visualisation dashboards to effectively communicate EY’s advice to clients.
• Capacity to communicate the business and non-technical implications of technical roadblocks and technical design decisions to non-technical clients.
• Experience in managing projects, from defining requirements, designing project plans, and managing performance against plan through the project lifecycle.
• Experience working with large datasets (creating databases, architecting efficient structures, and writing optimised stored procedures & queries).
• Experience in building models in R and Python programming languages and libraries in a client-facing role.
• Visually creative, with a good understanding of UX aesthetics.

Ideally you’ll also have some of the following

• Experience of financial reporting, and an understanding of basic corporate finance and accounting concepts.
• Experience of working in a professional services environment, including exposure to high-profile transactions.
• Knowledge and experience relating to one or more specific sectors is preferred.
• Experience of working with visualisation tools including Power BI, Tableau, Tibco Spotfire, RShiny, plotly-dash, D3.js, or QlikSense.
• Experience in SQL (any variant), Alteryx, MS Excel and VBA.
• Experience in applying various analytical techniques (e.g. naïve Bayes, decision trees, random forest, xgboost and k-means) to calculate problems such as predictive forecasting, prescriptive action, capacity planning.
• Experience of working in teams, managing the workload of junior team members, and coaching junior staff.

What EY-Parthenon Offers

• Exposure to high-impact deal environments and strategic projects.
• Opportunity to work with clients across industries.
• Strong focus on learning and development in both technical and consulting skills.
• A collaborative and fast-paced team environment.