At a Glance
- Tasks: Drive reliability metrics and influence engineering decisions for a seamless customer experience.
- Company: Join Wise, a global tech leader transforming how money moves worldwide.
- Benefits: Competitive salary, stock options, flexible work, and personal development budget.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make a real impact on millions of customers and shape the future of financial transactions.
- Qualifications: Strong SQL skills, data visualisation experience, and a passion for real-world impact.
The predicted salary is between 60000 - 95000 £ per year.
Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
Wise is on a mission to facilitate borderless transactions – instant, transparent, and eventually free. 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.
The Platform Engineering Tribe is the backbone of Wise's technical infrastructure, ensuring everything runs smoothly for our customers and engineering teams. 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. This role is responsible for reliability.
In this role, you will partner with senior engineering and product leaders to bring clarity to reliability: what it means in practice, how we measure it, and where we need to improve. 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. You’ll play a key role in ensuring reliability is built into how we design and operate systems from the outset, not treated as an afterthought. 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.
Success In This Role Means That:
- Reliability improves in measurable ways across the platform
- Teams make better, more informed decisions because of your work
- Leadership has a clear, consistent view of reliability and its impact on customers
About You:
We’re looking for someone who is obsessed with moving metrics, not just analysing them. We care far more about what you changed than what you built. You might be a strong analyst, product‑minded data scientist, or even an ex‑engineer, but what matters most is that you:
- Take ownership of outcomes, not just outputs
- Are comfortable operating in ambiguity and shaping problems
- Influence senior stakeholders without formal authority
- Care about real‑world impact more than perfect models
How You’ll Work:
- Own the Reliability metrics end‑to‑end: definition, measurement, targets, and progress
- Partner deeply with engineering: understand systems, incidents, and trade‑offs
- Drive decisions: bring clarity to complex problems and push for action
- Balance short vs long‑term: incidents vs systemic improvements
- Create leverage: frameworks, dashboards, and narratives that scale
Technical Expectations:
- 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
- Familiarity with observability/reliability concepts (SLIs, SLOs, incidents)
- Some experience with Python / data transformation (DBT, etc.) is helpful
Why Should You Join Our Team?
- Own a company‑level KPI: not a dashboard, but a real outcome
- High leverage: your work affects hundreds of engineers and millions of customers
- Complex, meaningful problems: distributed systems, real‑time failures, trade‑offs at scale
- Influence without authority: work directly with senior engineering leadership
Benefits:
- Salary: £60,000-£95,000
- Competitive stock options in a profitable company
- Flexible working conditions tailored to support a balance between work and personal life
- Annual budget for personal and professional development
Please note that Wise does not provide visa sponsorship for this role. Applicants must have the right to work in the UK.
Commitment To Diversity: Wise is dedicated to fostering a diverse and inclusive workplace. We strongly encourage applications from all backgrounds and are committed to providing equal opportunity in our employment practices.
Senior Data Analyst - Product Reliability employer: hackajob
Wise is an exceptional employer that prioritises employee growth and work-life balance, offering competitive salaries and stock options in a thriving global technology environment. With a strong commitment to diversity and inclusion, Wise fosters a collaborative culture where your contributions directly impact millions of customers and the company's mission to revolutionise money management. Join us in a role that not only challenges you but also empowers you to drive meaningful change in a dynamic and supportive setting.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst - Product Reliability
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Wise on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by diving deep into Wise's mission and values. Show us how your skills in data analysis and reliability align with what they’re all about. We want to see that passion!
✨Tip Number 3
Practice your storytelling skills! Be ready to share specific examples of how you've improved metrics or influenced decisions in past roles. We love hearing about real-world impact over just numbers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at Wise.
We think you need these skills to ace Senior Data Analyst - Product Reliability
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior Data Analyst role. Highlight your experience with reliability metrics and how you've influenced decisions in previous roles. We want to see how you can bring value to our mission!
Showcase Your Impact:When detailing your past experiences, focus on the outcomes rather than just the tasks you completed. We care about what you changed and how it benefited the team or company. Use metrics to back up your claims!
Be Clear and Concise:Keep your application straightforward and to the point. Avoid jargon unless it's relevant to the role. We appreciate clarity, especially when it comes to complex topics like reliability and data analysis.
Apply Through Our Website:We encourage you to submit your application directly through our website. This way, we can ensure your application gets the attention it deserves. Plus, it’s the best way to stay updated on your application status!
How to prepare for a job interview at hackajob
✨Know Your Metrics
As a Senior Data Analyst, you'll need to demonstrate your obsession with moving metrics. Be prepared to discuss specific examples of how you've influenced key performance indicators in previous roles. Show them you understand the importance of reliability and how it impacts customer trust.
✨Understand the Tech Stack
Familiarise yourself with the tools and technologies mentioned in the job description, like SQL, Looker, and DBT. During the interview, be ready to explain how you've used these tools to build data pipelines or visualise data effectively. This will show that you're not just a numbers person but also technically savvy.
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving skills in ambiguous situations. Think about past experiences where you had to make decisions based on incomplete information. Prepare to articulate how you approached these challenges and what the outcomes were, especially in terms of reliability improvements.
✨Engage with Stakeholders
Since influencing senior stakeholders is crucial, practice how you would communicate complex data insights to non-technical audiences. Prepare examples of how you've successfully collaborated with engineering teams or leadership in the past, highlighting your ability to drive decisions and create clarity around reliability.
