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Job Description & Summary

We are seeking an Associate Director to help lead and grow our Data & AI capability within Technology Consulting. The role will involve shaping and delivering client engagements across data strategy, analytics, BI, data engineering, data governance, data science and AI-enabled transformation.

The successful candidate will lead multi-disciplinary teams, manage senior client relationships, provide delivery oversight and support the continued development of our Data & AI practice. You will work with senior clients and internal leadership to shape Data & AI opportunities, build capability and support the continued growth of the practice. This role offers exciting opportunities for both technical and professional growth, as you help shape data-driven decision-making for a diverse portfolio of clients, across financial services, public sector, healthcare, life sciences and other data-intensive sectors.

Embrace the possibility to apply – you don’t need to meet every single requirement. We would love to hear from you!

Join a Dynamic Team Driving Change

Our Technology Consulting team is part our wider Consulting and Advisory services, made up of both industry leads and subject matter experts driving change and innovation across this ever-growing department. Our consultants possess transferable skills and collaborate across various teams within the Consulting, Advisory department, applying expertise in project management, stakeholder management, communication and process improvement to drive impactful results.

As a Data & AI Consultant, you will work alongside clients across diverse sectors, using your technical, analytical and consulting skills to deliver practical data and AI solutions. The role is hybrid, with client-site presence required where needed.

Role Tracks

Candidates are not expected to have equal depth across every Data & AI discipline. We are looking for an experienced consulting or industry data leader who can lead client engagements, shape practical solutions and bring depth in one or more of the following areas.

Depending on background and client demand, the Associate Director may lead or support work across one or more of the following role tracks.

Data Strategy, Operating Model and Transformation

This track is suited to candidates who help clients define their data direction, delivery model and transformation priorities. Work may include data strategy, roadmaps, business cases, operating models, governance structures, maturity assessments and delivery mobilisation.

Data Analytics, BI and Reporting Leadership

This track is suited to candidates who lead analytics, reporting and BI delivery. Work may include KPI design, reporting transformation, dashboard delivery, semantic modelling, self-service analytics, reporting controls and helping senior stakeholders use data to support decisions.

Data Engineering and Data Platform Leadership

This track is suited to candidates who lead data engineering, analytics engineering or data platform work. Work may include data pipelines, ETL / ELT, data warehouses, lakehouses, integration patterns, cloud data platforms, data modelling, data quality, testing and technical delivery oversight.

Data Science, AI and Advanced Analytics Leadership

This track is suited to candidates who shape and lead advanced analytics, machine learning or AI-enabled use cases. Work may include predictive modelling, optimisation, NLP, GenAI-enabled analysis, model validation, model monitoring, AI governance and translating analytical outputs into business action.

Data Governance, Data Quality and Data Management Leadership

This track is suited to candidates who lead governance, quality, control or remediation work. Work may include data governance frameworks, ownership models, stewardship, data quality assessments, metadata, lineage, data dictionaries, regulatory reporting support and data remediation programmes.

Automation and AI-enabled Workflow Leadership

This track is suited to candidates who lead automation, process improvement or AI-enabled workflow work. Work may include process assessment, workflow redesign, reporting automation, document processing, data extraction, classification, triage, operational controls and adoption planning.

The Associate Director may lead specialists across several of these tracks, provide quality assurance over delivery outputs and help translate client demand into clear Data & AI propositions, teams and delivery plans.

Roles and Responsibilities

As a Data & AI Consultant at Associate Director level, you will help lead the growth and delivery of Grant Thornton’s Data & AI capability within Technology Consulting. You will work with senior clients and internal teams to shape, sell and deliver Data & AI engagements across analytics, BI, data engineering, data governance, data science, AI and automation.

Responsibilities may include:

·       Leading client engagements across Data & AI, including strategy, mobilisation, design, delivery and implementation support.

·       Shaping client solutions across data analytics, BI, data engineering, data platforms, data governance, data science, AI and workflow automation.

·       Working with senior client stakeholders to understand business priorities, define problems and identify practical data-led solutions.

·       Leading multi-disciplinary delivery teams, including analysts, BI developers, data engineers, data scientists, governance specialists and automation consultants.

·       Providing quality assurance over client deliverables, including analysis, dashboards, technical documentation, data models, governance outputs, delivery plans and recommendations.

·       Translating technical work into clear business messages, recommendations and implementation plans for senior stakeholders.

·       Overseeing delivery planning, workstream management, risks, issues, dependencies, budgets and engagement economics.

·       Managing client relationships day to day and supporting Partners and Directors in account development.

·       Identifying new opportunities for Data & AI services with existing and prospective clients.

·       Leading or contributing to proposals, client presentations, solution materials, credentials and commercial responses.

·       Supporting the development of Data & AI propositions, methodologies, templates, accelerators and reusable delivery assets.

·       Coaching, mentoring and developing consultants across different Data & AI disciplines.

·       Supporting recruitment, onboarding and capability development across the Data & AI team.

·       Working with other Grant Thornton service lines and sector teams to bring Data & AI capability into wider consulting and advisory engagements.

·       Staying up to date with developments in data, analytics, AI, automation, governance, cloud platforms and relevant regulation.

·       Promoting strong delivery standards, including documentation, review, testing, governance, risk management and client communication.

Depending on background and client demand, the Associate Director may also:

·       Lead data strategy and operating model assessments.

·       Oversee BI, reporting and dashboard transformation programmes.

·       Lead data engineering, data platform or migration workstreams.

·       Shape advanced analytics, machine learning, NLP or GenAI use cases.

·       Lead data quality, governance, metadata or remediation programmes.

.       Lead AI-enabled automation and workflow improvement engagements.

Education and Certifications

·       Degree or equivalent experience in a relevant discipline such as Data Science, Computer Science, Engineering, Information Systems, Mathematics, Statistics, Economics, Business Analytics or a related field.

·       A minimum of 8 years’ professional experience in data, analytics, BI, data engineering, data science, AI, automation, data governance, technology consulting or a related field.

·       Proficiency in at least one programming language such as SQL, R or Python.

Preferred Qualifications

·       Additional certifications in Data Analytics, Data Science or Business Intelligence (e.g., Certified Analytics Professional, Microsoft Certified: Data Analyst Associate, Azure / AWS / GCP data certifications, Microsoft Fabric, Databricks, Snowflake, DAMA / data governance).

·       Advanced degrees (Master’s or PhD.) in Data Science, Statistics, Economics, Engineering or a related technical field.

Experience, Skills and Competencies

We are looking for an experienced Data & AI professional with strong delivery leadership, client management and technical credibility in one or more Data & AI disciplines. Candidates do not need to have equal depth across every technical area, but should be able to lead multi-disciplinary teams and shape client solutions across data, analytics, AI or governance.

Core experience and leadership skills

·       Typically 8+ years of experience in data, analytics, BI, data engineering, data science, AI, data governance, automation, technology consulting or a related field.

·       Proven experience leading Data & AI engagements, programmes, workstreams or teams in a consulting, professional services, industry or technology environment.

·       Strong ability to work with senior stakeholders to understand business priorities, define problems and shape practical data-led solutions.

·       Experience translating technical work into clear recommendations, delivery plans, business cases, roadmaps or client-ready outputs.

·       Strong communication and presentation skills, including the ability to explain complex technical topics to senior non-technical audiences.

·       Experience managing delivery risks, issues, dependencies, budgets, workplans and engagement economics.

·       Experience leading, coaching or developing junior team members.

·       Ability to provide quality assurance across technical and business deliverables.

·       Strong commercial awareness and an interest in supporting business development, proposals and account growth.

·       Experience working across multiple stakeholders, sectors, teams or service lines.

·       Experience in consulting, professional services or client-facing delivery is preferred.

·       Experience working in banking, insurance, asset management, healthcare, life sciences, public sector or other data-intensive sectors is beneficial.

·       Experience supporting business development, proposals, client presentations, commercial responses, account planning or proposition development is preferred.

·       Experience building internal capability, developing methodologies, creating reusable assets or supporting recruitment and onboarding is beneficial.

Data Strategy, Operating Model and Transformation

Candidates with a data strategy or transformation background may bring experience in some of the following areas:

·       Defining data strategies, roadmaps, business cases and delivery plans.

·       Designing data operating models, governance structures, roles, responsibilities and delivery approaches.

·       Leading data maturity assessments, discovery phases, mobilisation activity or current-state reviews.

·       Advising clients on how to improve data capability, reporting maturity, data quality or analytics adoption.

·       Translating business strategy, regulatory requirements or operational problems into Data & AI initiatives.

·       Supporting senior stakeholders through data-led change, implementation planning and adoption.

Data Analytics, BI and Reporting Leadership

Candidates with a BI or analytics leadership background may bring experience in some of the following areas:

·       Leading the design and delivery of BI, reporting, dashboarding or management information solutions.

·       Overseeing KPI definition, reporting requirements, semantic modelling and dashboard design.

·       Providing quality assurance over Power BI, Tableau, Qlik, Excel or other reporting outputs.

·       Supporting reporting automation, self-service analytics and analytics adoption.

·       Improving reporting governance, access management, refresh processes, documentation and controls.

·       Helping senior stakeholders interpret analytical outputs and use data to support decisions.

Data Engineering and Data Platform Leadership

Candidates with a data engineering, analytics engineering or platform background may bring experience in some of the following areas:

·       Leading the design and delivery of data pipelines, ETL / ELT workflows and data platform components.

·       Advising on data warehouse, data lake, lakehouse, integration or cloud data platform approaches.

·       Working with technologies such as Azure, AWS, GCP, Microsoft Fabric, Databricks, Snowflake, Oracle, SQL Server, IBM DB2, Teradata or similar.

·       Overseeing data modelling, data quality, reconciliation, lineage, testing and technical documentation.

·       Providing delivery oversight across engineering teams, including planning, review, risk management and stakeholder communication.

·       Supporting reliable data delivery through appropriate development, testing, deployment and operational controls.

Data Science, AI and Advanced Analytics Leadership

Candidates with a data science, AI or advanced analytics background may bring experience in some of the following areas:

·       Leading the development of statistical, predictive, machine learning, optimisation, NLP or GenAI-enabled use cases.

·       Advising clients on where AI, machine learning or advanced analytics can be applied responsibly and practically.

·       Overseeing model design, feature engineering, validation, testing, performance evaluation and interpretation.

·       Supporting model deployment, monitoring, governance and adoption.

·       Translating analytical and model outputs into clear business recommendations and implementation plans.

·       Applying responsible AI principles, including explainability, transparency, fairness, appropriate human oversight and data protection.

·       Understanding of model risk, AI governance or regulatory considerations is beneficial.

Data Governance, Data Quality and Data Management Leadership

Candidates with a data governance, data quality or data management background may bring experience in some of the following areas:

·       Designing data governance frameworks, ownership models, stewardship approaches and data control processes.

·       Leading data quality assessments, remediation programmes, data dictionary development and lineage documentation.

·       Supporting data migration, regulatory reporting, system implementation or data control projects.

·       Advising clients on metadata, business glossaries, data standards, data quality rules and controls.

·       Helping clients improve confidence in data used for reporting, analytics, regulatory submissions and operational decision-making.

·       Working with senior stakeholders to embed governance into day-to-day business and technology processes.

Automation and AI-enabled Workflow Leadership

Candidates with an automation or workflow improvement background may bring experience in some of the following areas:

·       Identifying automation and AI-enabled workflow opportunities across reporting, operations, risk, finance, compliance, customer or back-office processes.

·       Leading process assessment, redesign and automation delivery using tools such as Power Automate, Power Apps, UiPath, Python, VBA or similar platforms.

·       Advising on the use of AI for document processing, classification, data extraction, triage, workflow routing or decision support.

·       Ensuring automation solutions include appropriate controls, testing, documentation, handover and adoption support.

·       Moving automation or AI use cases from discovery and proof of concept into sustainable delivery.