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WISE

Platform Engineer - Analytics Platform

Posted 9 Hours Ago
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Hybrid
London, Greater London, England
Mid level
Hybrid
London, Greater London, England
Mid level
As a Platform Engineer on the Analytics Platform team, you'll enhance the infrastructure of the data platform to ensure high performance and reliability. This involves implementing observability frameworks, maintaining data flows across systems, and collaborating with cross-functional teams. You'll also work on the ELT move to an orchestrated Airflow deployment, ensuring alignment in data serving and availability.
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Company Description

Platform Engineer - Analytics Platform

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 life 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. For everyone, everywhere.

More about our mission.

Job Description

About the role 

Our team: the Analytics Platform team, on the Data Squad

For our customers, using Wise is as simple as sending money from A to B. Yet behind our app and website is a complex engine of currencies, routes, products and features, generating terabytes of data each day. The Data services offered by the Data Squad is at the core of systems that store, process and leverage this data, ultimately providing real time decision making capabilities that serve as one of many drivers for business growth. 

As a Platform Engineer, you will be integral to maintaining and enhancing the data platform's infrastructure to ensure high performance, scalability, and reliability. You will have the opportunity to leverage technologies, such as Airflow, Iceberg, and Trino, to drive strategic initiatives and support the evolving needs of our organisation.

We also manage a deployment of PipelineWise (https://transferwise.github.io/pipelinewise/), an initiative which started with this team, as well our Snowflake-based data warehouse governance and the analytics dashboarding tools we have in place. 

These systems are deployed either on an internally run Kubernetes cluster or run by the team on AWS components, eventually to be ported across to internally maintained solutions. We’re now starting off the migration to an orchestrated solution (K8s-based) and we need help to achieve this!

How we work

At Wise we believe in automation, programmatic implementation, and reusable design. We’re looking for people who can step back and think holistically about the ecosystem, but also follow through and help implement the design; drawing on the resources across the rest of the platform tribe.

As we grow, we must prioritise protecting our customers’ money and there are many challenges when it comes to meeting regulatory requirements world-wide. You will have a focus on running and maintaining the analytics services, making sure we have the right observability and service management elements in place, with an eye for high-availability, assessing and reducing engineering load and devising more effective ways for the team to look after its cloud-based platform.

We need to sustain this growth by continuously iterating on the services we run, with a focus on availability, security, and ease of use. We’re looking for an engineer with relevant experience who can analyse complex requirements and deliver simple solutions to help our teams achieve our mission with speed and confidence.

We are looking for candidates with a minimum of 4 years of relevant experience for this role. Whilst we appreciate all applications, please note that candidates who do not meet this requirement will not be considered.

What will you be working on?

  • Maintain and enhance the infrastructure supporting the data platform, ensuring high performance and availability.

  • Ensure the reliability and scalability of data flows across various systems and services.

  • Implement robust observability and alerting frameworks using tools such as Prometheus and Grafana.

  • Collaborate with cross-functional teams, including Analytics Experience and Data Governance, to ensure alignment in data serving and consumption patterns.

  • Help establish and maintain high-standard service level agreements (SLAs) for data availability, system responsiveness, and incident management.

  • Participate in the development and improvement of onboarding processes to promote a seamless user experience.

  • Design, execute, and support the ELT move to an orchestrated Airflow deployment.

What do you need?

If you have some of the skills listed below and are eager to learn more we do want to hear from you!

  • Experience as an engineer during which you developed skills in container technologies like Docker or Kubernetes.

  • Infrastructure-as-code is a necessity of our daily operations, Wise uses Terraform but it’s more important the candidate is familiar with the concept and prioritises this practice in his/her work.

  • Experience running large data systems and production services in the cloud (AWS preferred)

  • Strong fundamentals in distributed systems design and development.

  • Familiarity with GitOps and Airflow is a big plus.

  • Proficiency in one or more programming languages (Python or Java preferred)

  • A good understanding of relational databases, big data, and stream processing technologies. These can vary but typically you’d find tools like Kafka, Spark, Snowflake, etc..

  • Good grasp of fundamental software engineering practices like good design documentation, unit testing, peer code reviews, and a preference for agile methods

  • Communication, presentation, interpersonal and organisational skills to communicate effectively new processes and workflows, and interact with teams from different areas of the organisation

Nice to Have

  • Experience with tooling in the Observability space such as Grafana (other tools like New Relic or Kibana, etc.., are also taken into consideration).

  • Familiarity with deploying and/or managing Analytics tools such as Looker and Superset.

  • Experience in building self-service tooling within the organisation that helps engineers, analysts or data scientists do their job more efficiently

Interested? Find out more:

  • The Wise Tech Stack, 2025 Edition.

  • Scaling our Infrastructure; how we make it work

  • Wise Engineering – https://medium.com/wise-engineering

What do we offer: 

  • Starting salary: £80,000-£102,000 + RSU

  • Wise Benefits

#LI-AB3 #LI-Hybrid

Additional Information

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.

Top Skills

Java
Python

WISE London, England Office

London, United Kingdom

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