At a Glance
- Tasks: Lead and mentor data engineers while shaping the data infrastructure at Wise.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, stock options, flexible working, and generous leave policies.
- Other info: Diverse and inclusive team culture with excellent career growth opportunities.
- Why this job: Make a real impact by building better products through data insights.
- Qualifications: Advanced SQL and Python skills, with experience in data modelling and project leadership.
The predicted salary is between 85000 - 125000 £ 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. As part of our team, you will be helping us create an entirely new network for the world's money.
We're looking for a Lead Analytics Engineer to join our Analytics Experience team in London. Your mission is to help us build better products, faster by making it easy for Wisers to get insights from data. At Wise, we have over 130 Analysts and more than 2,500 weekly active users of our Business Intelligence Tools. As a Lead Analytics Engineer, you'll be crucial in ensuring it's easy to find the right data quickly.
Here’s how you’ll be contributing to the Analytics Engineering team:
- Lead and Mentor: You will work closely with Analysts within one of Wise's squads, spending significant time mentoring them directly to establish best practices around infrastructure, monitoring, testing, and data modelling.
- Strategic Roadmap: You will take ownership of defining and driving the data infrastructure roadmap for your assigned tribe, ensuring strategic alignment and efficient execution.
- Core Data Sets: You will play a key role in building and maintaining core datasets, ensuring data quality and accessibility.
- Tooling Evangelist: Become the go-to expert for new tooling like dbt & AI applications, leading its adoption and successful rollout across the organization.
- Best Practices Driver: Strategically assess and implement data modelling best practices within your squad, elevating our data capabilities.
Qualifications:
- Technical Expertise: Advanced proficiency in SQL and Python is a must.
- Data Pipelining & Modelling: Proven experience in building robust analytics pipelines and designing effective data models.
- Orchestration Mastery: Hands-on experience using an orchestration tool like Airflow.
- Project Leadership: Strong capabilities in project management and communication, with a track record of driving initiatives.
- Impactful Storytelling: Excellent storytelling ability with data, translating complex insights into clear, actionable narratives.
- Python Development: Demonstrated ability to build practical solutions using Python.
- Stakeholder Empathy: You’re able to build strong empathy for your stakeholders and internal customers, proactively identifying and solving their problems.
- BI Tooling: A driver of best practices regarding Business Intelligence Tools like Looker or Superset.
Our Offer:
- Base salary: £85-125k gross / year base (based on experience & interview outcomes)
- Restricted Stock Units (RSUs)
- Numerous amount of best in class benefits
- Flexible working - whether it’s working from home, school plays or life admin we get that flexibility is essential and you’re trusted to do the right thing and be responsible
- Paid annual holiday, sick days, parental leave and other leave opportunities
- 6 weeks of paid sabbatical after 4 years at Wise on top of annual leave
For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they’re diverse, equitable and inclusive. We’re proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs. Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Lead Analytics Engineer — Mentor Data Engineers & Shape Infra employer: hackajob
Wise is an exceptional employer that prioritises employee growth and inclusivity, offering a dynamic work culture in London. As a Lead Analytics Engineer, you will benefit from flexible working arrangements, competitive salaries, and a generous sabbatical policy, all while being part of a diverse team dedicated to revolutionising the way money is managed globally. With ample opportunities for mentorship and professional development, Wise empowers its employees to thrive and make a meaningful impact in the fintech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Analytics Engineer — Mentor Data Engineers & Shape Infra
✨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 brushing up on your SQL and Python skills. We know these are crucial for the Lead Analytics Engineer role, so practice coding challenges and be ready to showcase your expertise.
✨Tip Number 3
Showcase your storytelling skills with data during interviews. We want to see how you can translate complex insights into clear narratives that resonate with stakeholders. Bring examples of your past work!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Wise team.
We think you need these skills to ace Lead Analytics Engineer — Mentor Data Engineers & Shape Infra
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your technical expertise in SQL and Python right from the get-go. We want to see how your experience aligns with the role, so don’t hold back on showcasing your data pipelining and modelling skills!
Tell a Story with Data:When you describe your past projects, focus on how you turned complex data insights into clear narratives. We love impactful storytelling, so share examples that demonstrate your ability to communicate effectively with stakeholders.
Be a Team Player:Since mentoring is a big part of this role, let us know about your experience working collaboratively with others. Share instances where you’ve led initiatives or helped teammates improve their skills – we’re all about building each other up!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, you’ll find all the info you need about the role there!
How to prepare for a job interview at hackajob
✨Know Your Data Inside Out
As a Lead Analytics Engineer, you'll need to demonstrate your technical expertise in SQL and Python. Brush up on your skills and be ready to discuss specific projects where you've built robust analytics pipelines or designed effective data models. Show them you can not only talk the talk but also walk the walk!
✨Showcase Your Mentoring Skills
Since mentoring is a key part of this role, prepare examples of how you've successfully guided others in best practices around data infrastructure and modelling. Think about specific instances where your mentorship led to improved outcomes for your team or project.
✨Be a Tooling Evangelist
Wise is looking for someone who can lead the adoption of new tools like dbt and AI applications. Familiarise yourself with these tools and be prepared to discuss how you've implemented similar technologies in past roles. Highlight your ability to drive change and improve processes through innovative solutions.
✨Master the Art of Storytelling with Data
Your ability to translate complex insights into clear narratives will be crucial. Prepare to share examples of how you've communicated data-driven insights to stakeholders. Practice telling a compelling story that showcases your analytical skills and how they can benefit Wise's mission.