Lead Data Analyst

We are currently seeking an experienced Lead Data Analyst / Data Product Lead to join a growing data and technology consulting practice, delivering high-impact analytics, reporting, and data transformation solutions across a diverse range of public and private sector clients.

This role is ideal for a senior data professional who combines strong analytical expertise with leadership capability and can effectively bridge the gap between business stakeholders, data teams, and technical delivery functions. You will lead multidisciplinary teams, shape data products from concept through to implementation, and help organisations unlock greater value from their data using modern cloud-based technologies.

Due to the nature of some client engagements, candidates should ideally hold active SC Clearance or have held SC Clearance within the last 12 months and be eligible for re-clearance.

As a Lead Data Analyst / Data Product Lead, you will be responsible for delivering business-critical analytical outcomes as part of large-scale data and transformation programmes. Working closely with business stakeholders, architects, engineers, and delivery teams, you will define requirements, prioritise workstreams, and oversee the successful delivery of data-driven solutions.

You will act as a trusted advisor, helping clients align business goals, data strategy, and technology investments to achieve measurable outcomes.

• Lead analytical and data-focused delivery workstreams across complex transformation programmes.
• Own analytical roadmaps and delivery plans within broader data platform and modernisation initiatives.
• Manage, mentor, and develop teams of analysts, analytics engineers, and data engineers.
• Establish best practices for requirements gathering, documentation, testing, governance, code quality, peer reviews, and release management.
• Facilitate workshops to capture business requirements, map data processes, align stakeholders, and define success criteria.
• Partner with stakeholders across Product, Operations, Finance, Risk, and Technology functions to prioritise initiatives and drive adoption.
• Define acceptance criteria and maintain quality standards for reporting and analytical solutions.
• Promote best practices in analytics, AI, cloud technologies, and modern data delivery.
• Support business development activities, including solution design, proposal creation, effort estimation, and project planning.
• Create reusable frameworks, delivery methodologies, and accelerators for future projects.
• Champion strong consulting principles, including collaboration, accountability, pragmatism, and client-focused delivery.

• Significant experience leading analytical product delivery or data-focused teams within complex enterprise environments.
• Proven track record delivering cloud-based data platforms, modern analytics solutions, reporting transformations, and data warehouse or lakehouse initiatives.
• Strong experience in migration validation, data reconciliation, data controls, and go-live readiness activities.
• Ability to manage multiple stakeholders and competing priorities across business and technical teams.
• Experience mentoring analysts and working closely with architects, engineers, and delivery leads.
• Excellent communication and stakeholder-management skills, with the ability to engage audiences at all organisational levels.
• Experience working within highly regulated or governance-heavy environments, ideally including government or regulated sectors.

• Advanced SQL and Python skills.
• Strong analytical and problem-solving capability.
• Data modelling expertise, including dimensional modelling and enterprise data concepts.
• Experience delivering business intelligence, dashboarding, and reporting solutions.
• Strong understanding of data governance, metadata management, lineage, and data quality principles.

Experience with one or more of:

• Microsoft Fabric
• Databricks
• Snowflake
• AWS Data Services
• Azure Data Services
• Google Cloud Platform (GCP)

• dbt or equivalent transformation frameworks.
• CI/CD implementation and release management practices.
• Version control and code review methodologies.
• Experience delivering within modern DataOps environments.

Experience with tools such as:

• Airflow
• Azure Data Factory (ADF)
• Dagster
• Similar data orchestration and monitoring platforms

Experience with:

• Power BI
• Tableau
• Looker
• Semantic modelling and metrics layer concepts

• Scrum, Kanban, SAFe, or similar agile frameworks.
• Sprint planning, backlog management, retrospectives, and delivery governance.
• Experience using Azure DevOps, Jira, Confluence, SharePoint, or equivalent collaboration platforms.

• Degree in a technical, analytical, scientific, or related discipline.
• Professional certifications in cloud, analytics, AI, data engineering, or data science.
• Certifications across Azure, AWS, Snowflake, Databricks, or GCP.
• Agile certifications such as Scrum Master or SAFe Agilist.
• Cloud architecture certifications are advantageous.