Data Analyst

Overview

A growing consultancy working across UK and EU is hiring a Data Analyst on a permanent basis. The role is fully remote-first, with occasional client site visits of one to two days per month. Salary is £65,000 - £75,000.

This role exists because the business needs someone who can sit at the intersection of client stakeholders and technical delivery teams, and make both sides work better together. Day to day, that means running workshops, gathering and translating requirements, profiling and modelling data, and making sure what gets built actually holds up against what the client asked for. The business runs modern cloud-native stacks across its projects, so you will move between tools and contexts regularly. What makes this role genuinely interesting is the scope: you own the full analytical pipeline from first conversation with a client through to delivery, and you are expected to think like a strategic partner, not just an executor. If you want variety, real accountability, and the chance to work with high-performing teams on projects that are run well, this is a strong opportunity.

Key Responsibilities

• Gather, document, and translate business and project requirements from client stakeholders
• Run stakeholder workshops and manage stakeholder mapping across seniority levels, including C-suite
• Profile, analyse, and cleanse large and complex datasets
• Create conceptual, logical, and physical data models, including lakehouse and warehouse modelling
• Produce data mapping specifications for migrations
• Build and manage team backlogs using tools such as Jira or Azure DevOps
• Coordinate UAT with business stakeholders and ensure delivery holds up against requirements
• Design data storage solutions appropriate to client environments
• Build data dashboards and reports in Power BI, Qlik, or Looker, with clear narrative storytelling
• Work across cloud platforms (Azure, AWS, GCP) and modern tooling including Databricks, Snowflake, and dbt

Requirements

Must-haves

• Strong SQL skills, hands-on and demonstrable
• Python proficiency, particularly pandas
• Conceptual, logical, and physical data modelling experience
• Requirements gathering and stakeholder management across seniority levels
• UAT coordination with business stakeholders
• Backlog management using Jira or Azure DevOps
• Familiarity with OLTP and OLAP systems
• Experience with at least one major cloud platform (Azure, AWS, or GCP)
• Comfortable presenting and communicating at C-suite level
• Able to operate with low context, build trust quickly, and work independently

Nice-to-haves

• Experience with Databricks, Snowflake, or dbt
• Familiarity with Power BI, Qlik, or Looker
• Prior consulting or client-facing delivery experience
• Strategic thinking beyond the immediate task, with a track record of influencing decisions

What Success Looks Like

• Delivered at least one project end to end, from requirements gathering through to technical delivery
• Held accountability for ensuring the technical output meets what the client actually asked for
• Built trusted relationships with client stakeholders independently, without heavy internal support
• Navigated at least one context switch between clients or tech stacks without losing momentum
• Recognised by the team and by clients as someone who adds strategic value, not just analytical output

Team and Culture

• Remote-first in practice, with no fixed office requirement and a working pattern built around flexibility
• Teams are assembled thoughtfully, with a genuine effort to keep high-performing groups together across projects
• The business takes workload and wellbeing seriously, with structured support including mental health provision and flexible arrangements
• Agile and scrum are the default ways of working across all projects

Challenges

• Consulting contexts mean being dropped into new client environments regularly, often with limited background, and needing to build credibility fast
• Stakeholder buy-in is rarely a given: influencing decisions and earning trust are active, ongoing parts of the job
• Flipping between different tech stacks and client contexts is the norm, not the exception, so adaptability is genuinely tested
• The role demands proactive, independent judgment: waiting to be directed is not a comfortable way to operate here