Lead Data Analyst (Lead I - Data Engineering)

We are seeking an experienced Lead Data Analyst to join our client’s Data team. This role combines advanced analytical capabilities with stakeholder engagement and data governance expertise. You will work closely with business stakeholders, Data Engineers, Architects, and Product teams to deliver high-quality insights, support strategic decision-making, and drive data excellence across the organisation., Data Analysis & Insight Generation

• Analyse business and operational data to identify trends, insights, risks and opportunities.
• Develop clear and actionable recommendations based on data analysis.
• Support the creation and maintenance of dashboards, reports and datasets that enable informed decision-making.
• Define, track and report on key performance indicators and success metrics.
• Work with stakeholders to understand data requirements and translate them into meaningful analytical outputs.

Data Quality & Governance

• Ensure data quality and integrity across the full data lifecycle, from source systems through to reporting and analytics.
• Conduct data validation, reconciliation and quality assurance activities to identify and resolve data issues.
• Support the definition and implementation of data quality rules and controls.
• Assist with documenting data lineage, transformations and business definitions to support transparency and trust in data.
• Promote best practices for data governance, accuracy and consistency.

Data Modelling & Architecture Support

• Support the design, development and maintenance of logical and physical data models across business domains.
• Assist with dimensional modelling activities, including fact and dimension design using Kimball methodologies.
• Support the documentation and maintenance of Data Vault models within raw and business integration layers.
• Help define and document data flows, business entities and relationships across enterprise systems.
• Contribute to the ongoing development of architecture standards, principles and modelling best practices.
• Support metadata management, data catalogue and data discoverability initiatives.

Requirements & Business Engagement

• Engage with business stakeholders to understand requirements, pain points and opportunities.
• Translate business requirements into clear and technically viable data specifications.
• Collaborate with Engineers, Architects and Product teams to ensure solutions meet business needs.
• Support workshops, discovery activities and requirement gathering sessions.
• Maintain clear traceability between user requirements and delivered data products.

Collaboration & Communication

• Work closely with Data Architects, Data Engineers, Product Managers and Business stakeholders to deliver effective data solutions.
• Produce clear documentation, presentations and recommendations suitable for technical and non-technical audiences.
• Communicate findings, insights and proposed solutions in a concise and engaging manner.
• Support adoption and understanding of data products through training, documentation and stakeholder engagement

• Strong analytical skills with the ability to interpret complex datasets and translate findings into actionable insights.
• Proficiency in SQL with experience querying, validating and analysing data directly from databases.
• Experience working with reporting tools, dashboards, performance metrics and analytical datasets.
• Understanding of data quality principles, validation techniques and governance processes.
• Ability to gather and document business requirements and translate them into technical solutions.
• Strong problem-solving and critical-thinking capabilities.
• Excellent written and verbal communication skills.
• Experience using Microsoft Excel and data visualisation tools such as Power BI.
• Ability to manage multiple tasks and priorities in a fast-paced environment.

Desirable

• Understanding of dimensional modelling techniques, including fact and dimension modelling.
• Exposure to Kimball methodology and data warehousing concepts.
• Understanding of Data Vault principles and modern data architecture practices.
• Experience documenting data lineage, metadata and business definitions.
• Familiarity with cloud-based data platforms and analytics ecosystems.
• Understanding of data governance, master data and enterprise data management concepts.
• Experience working in Agile delivery environments.
• Exposure to data catalogue or metadata management tools.
• Experience using Databricks for querying, analysing and transforming data within cloud-based analytics environments.