Data Analyst - Customer Success

RedCat Digital; England; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading digital analytics firm is seeking a Senior Data Analyst to join their Customer Success team. The ideal candidate will have over 8 years of experience in data analytics and be proficient in SQL, ETL pipelines, and modern BI tools. This role requires strong analytical skills to identify performance drivers and deliver actionable insights. The position is hybrid, based in London, offering a competitive rate of £285 per day for a 9-month contract.

Qualifications

• 8+ years’ experience in Data Analytics or Data Science.
• Expert-level SQL for data manipulation and analysis.
• Experience with big data platforms like Snowflake or Databricks.

Responsibilities

• Develop data pipelines and improve data integrity.
• Build scalable dashboards to deliver insights.
• Identify performance drivers and translate findings into actionable recommendations.

Skills

SQL

Data storytelling

Analytical thinking

ETL/data pipelines

Statistical methods

Python

BI tools

Tools

Power BI

Tableau

Snowflake

Databricks

Job description

Senior Data Analyst – Customer Success

£285/day | 9-Month Contract

Hybrid (London office 3 days, 2 days remote)

Join a Global Customer Success Data Science Team

We’re looking for an experienced Senior Data Analyst to help shape the future of customer experience and operational excellence across multiple international markets. If you love working end-to-end across the data lifecycle, building pipelines, defining metrics, analysing customer behaviour, and influencing strategy, this is an opportunity to make a real global impact.

💡 About the Role

You’ll join a high-impact Customer Success Data Science team partnering with Product, CX, Operations, Digital, and regional market teams. Your work will directly improve customer experience, drive measurable outcomes, and enable smarter decisions at scale.

We’re looking for someone with full-stack analytical capability across SQL, Python/R, BI tools, experimentation, and metrics engineering—someone who can transform complex data into clarity, action, and strategy.

🔧 What You’ll Do

• Build strong data foundations: Develop data pipelines, improve data integrity, and establish clear metric definitions and governance across regions.
• Automate and streamline reporting: Build scalable dashboards and reporting tools to deliver timely, accurate insights to business and Customer Success teams.
• Deliver deep-dive analytics: Identify performance drivers, customer pain points, and operational inefficiencies; translate findings into actionable recommendations.
• Support experimentation: Analyse A/B tests and digital experience initiatives to measure impact and guide continuous improvement.
• Tell the story with data: Communicate insights to technical and non-technical audiences, influencing strategy at regional and global levels.

🎯 What We’re Looking For

• 8+ years’ experience in Data Analytics or Data Science (Customer Success, Operations, or Digital Experience preferred).
• Expert-level SQL and strong experience with ETL/data pipelines.
• Proficiency with modern BI tools (Power BI, Tableau, Looker, Qlik).
• Experience with big data platforms such as Snowflake, Databricks, BigQuery, or Spark.
• Working knowledge of Python or R for analytics or automation.
• Strong understanding of statistical methods, experimentation, and A/B testing.
• Exceptional data storytelling and stakeholder communication skills.
• Experience with contact centre or digital support metrics is a plus.
• A proactive, growth-oriented mindset and the ability to balance strategic and tactical work.

✨ Why Join?

• Shape global Customer Success strategy with data
• Work across multiple regions and business functions
• Build foundations that influence customer outcomes at scale
• Lead meaningful analytics that drives real impact
• Join a team that values ownership, curiosity, and innovation

📍 Contract Details

• 💼 Duration: 9 months
• 💰 Rate: £285/day (Inside IR35)
• 📍 Location: London
• 🕒 Hybrid: 3 days in office, 2 days remote