At a Glance
- Tasks: Join Wise as a Senior Data Engineer and shape the future of global money management.
- Company: Wise, a diverse tech company on a mission to simplify international payments.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with a global team and enjoy a dynamic work environment.
- Why this job: Make a real impact by building scalable data systems that attract millions of customers.
- Qualifications: Strong Python skills and experience in data architecture and big data pipelines.
The predicted salary is between 70000 - 85000 £ per year.
This job is with Wise, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. 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.
About the role
We’re looking for a seasoned, senior Data Engineer with a strong software engineering background to join our Scalable Growth team within the Global Product Tribe. In this role, you’ll report directly to the Scalable Growth Engineering Lead while embedding day-to-day with the Marketing Platform team. You will serve as the technical authority on data architecture, bridging the gap between platform engineering and analytics engineering. You’ll bring maturity, resilience, and scalability to our data infrastructure—building and shaping systems that handle high-volume streaming and batch data to fuel our global marketing engine.
If you thrive in an environment where you can scope complex problem spaces, mentor engineers in data best practices, and directly impact how Wise attracts millions of customers globally, this is the role for you.
How we work
Scalable Growth is dedicated to building enabling technology that helps Wise acquire customers at the lowest possible cost. Within this space, the Marketing Platform team owns the data pipelines, internal tools, and integrations with third-party vendors (e.g., Meta, Google) that power our acquisition channels. As our dedicated data lead, you’ll work cross-functionally with engineers, product managers, digital analytics leads, and marketing stakeholders (Paid, Organic, CRM) to transform our marketing data infrastructure into a true platform product.
What will you be working on?
- Drive Data Architecture & Resilience: Audit, map out, and elevate our current data pipelines and streaming architectures. Establish best practices for monitoring, reliability, and scale across our data ecosystem (using Python, dbt, Airflow, Kafka, and Trino/Iceberg).
- Build the Unified Customer View: Productionize PoCs into scalable Airflow/dbt data workflows to lay the groundwork for our Customer Data Platform (CDP) datasets.
- Bridge Engineering & Analytics: Partner with analytics leads to define clear boundaries and standards for data ingestion, cleansing, and transformation—bringing a strong analytics engineering mindset (specifically via dbt) to raw data landing.
- Own MarTech Infrastructure: Work alongside Engineering Leads to bring technology ownership of MarTech systems (e.g., Braze, HighTouch reverse ETL) in-house, building end-to-end solutions rather than isolated data plumbing.
- Technical Scoping & Discovery: Take ownership of broad, ambiguous problem spaces. Uncover hidden challenges, propose robust architectural designs, and execute your own roadmap.
- Coach & Mentor: Elevate the data capabilities of software engineers in the squad through code reviews, architectural guidance, and hands-on mentoring.
Qualifications
What do you need? We are fully aware that it is uncommon for a candidate to have all skills required, and we fully support everyone in learning new skills with us. So if you have some of those listed below and are eager to learn more, we do want to hear from you!
- Python & Big Data Expertise: Advanced proficiency in Python and proven experience architecting, deploying, and maintaining Big Data and streaming/batch pipelines (e.g., Kafka Streams, Event Streaming, Trino, Iceberg).
- dbt & Airflow Proficiency: Hands-on experience using dbt for scalable data transformations and Airflow for workflow orchestration.
- Data Architecture Mastery: A strong background in designing scalable, fault-tolerant data architectures, implementing data quality frameworks, and establishing production best practices.
- Product & Discovery Mindset: Ability to take a vague problem statement, independently uncover the requirements, scope project milestones, and drive solutions end-to-end.
- Cross-functional Stakeholder Management: Excellent communication skills with the ability to bridge tech, marketing, and analytics, turning marketing needs into crisp engineering roadmaps.
Nice to Have:
- Experience with MarTech tooling or reverse ETL setups (e.g., HighTouch, Braze, vendor API integrations).
- Familiarity with modern AI/ML data integration practices.
- Background in fintech or fast-scaling tech platform environments.
Additional Information
Interested? Find out more: Wise Tech Stack, Wise Engineering Blog, Engineering career map. For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are 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.
Senior Data Engineer - Scalable Growth employer: Wise
Wise is an exceptional employer that prioritises the well-being and professional growth of its employees. With a dynamic work culture that fosters innovation and collaboration, team members are encouraged to develop their skills while contributing to meaningful resilience strategies on a global scale. Located in a vibrant city, Wise offers competitive benefits and unique opportunities for career advancement, making it an ideal place for those seeking a rewarding and impactful career.
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We think this is how you could land Senior Data Engineer - Scalable Growth
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Wise.
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We think you need these skills to ace Senior Data Engineer - Scalable Growth
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Wise, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Wise. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Wise
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Wise!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
