At a Glance
- Tasks: Analyse data to enhance platform reliability and influence key business decisions.
- Company: Join Wise, a global tech leader transforming how money moves.
- Benefits: Competitive salary, personal development budget, and commitment to diversity.
- Other info: Be part of an inclusive team dedicated to innovation and career growth.
- Why this job: Make a real impact on customer trust and business performance in a dynamic environment.
- Qualifications: Strong SQL skills, experience with data visualisation tools, and some Python knowledge.
The predicted salary is between 50000 - 60000 £ per year.
Wise is a global technology company, building the best way to move and manage the world’s money. As part of our team, you will be helping us create an entirely new network for the world's money. Behind our seamless customer experience is a complex system of services that process over $100 billion annually for 16+ million customers worldwide. As we scale to serve millions more customers, reliability isn’t just a technical concern, it’s core to customer trust and business performance.
Our Reliability squad combines expertise in systems availability and uptime, monitoring performance metrics, and developing robust applications, to create a resilient platform that our customers can depend on 24/7/365. Our impact is indirect but critical: when Platform works well, every product team ships faster, safer, and at lower cost. We operate around four north-star KPIs: Productivity, Cost Efficiency, Risk, and Reliability. You will connect low-level system signals: incidents, performance, failure modes, to their impact on customers and the business, and use that understanding to shape decisions. This includes identifying where we are falling short, highlighting the most important risks, and influencing how teams invest their time between building new capabilities and strengthening existing systems.
You might be a strong analyst, product-minded data scientist, or even an ex-engineer, but what matters most is that you:
- Balance short vs long-term: incidents vs systemic improvements
- Excellent SQL proficiency and experience with data visualization tools like Looker, Grafana, Lightdash, or Superset
- Ability to build and manage data pipelines that are modularised and scalable, using tools like DBT and Airflow
- Some experience with Python / data transformation (DBT, etc.) This is not a data engineering role, depth in pipelines is less important than impact on decisions.
Commitment to Diversity: If you're passionate about using your analytical skills to enhance platform reliability within a leading international financial services company, apply now to join us at Wise!
