Senior BI & Analytics Lead

RWS; Maidenhead; On-site; GBP 65,000 - 85,000; Full time

Job summary

RWS is seeking a Lead Analyst to join the Data and Analytics team in the United Kingdom. You will build strong stakeholder relationships, gather requirements, design SQL data structures, and develop dashboards using Sisense and other BI tools.

You will translate business needs into data-driven solutions and guide cross-functional teams to deliver high-quality insights. You will engage with stakeholders to identify opportunities for improvement, present findings, and ensure that data outputs

Qualifications

• Experience gathering requirements and documenting business needs.
• Ability to design and model data structures for reporting.
• Experience with data visualization and dashboard design.
• Strong stakeholder liaison and communication skills.
• Experience with data governance and security considerations is a plus.

Responsibilities

• Build strong stakeholder relationships to define business requirements.
• Lead information gathering and present findings to stakeholders.
• Design and build SQL data structures to prepare reports.
• Develop dashboards in Sisense and other BI tools.
• Collaborate with business teams to enable data-driven decisions.
• Identify performance and reporting challenges and propose improvements.
• Liaise with clients to understand data content.

Skills

T-SQL

BI tools (Sisense/Power BI/Looker)

Data warehousing

Cloud platforms (GCP/Azure)

Excel

Analytical thinking

Communication & presentation

Project management

Tools

Sisense

Power BI

Looker

Tableau

Excel

SQL Server

Job description

RWS is seeking a Lead Analyst to join the Data and Analytics team in the United Kingdom. You will build strong stakeholder relationships, gather requirements, design SQL data structures, and develop dashboards using Sisense and other BI tools.

You will translate business needs into data-driven solutions and guide cross-functional teams to deliver high-quality insights. You will engage with stakeholders to identify opportunities for improvement, present findings, and ensure that data outputs