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

We operate on a strong belief 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, it is imperative to protect 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. 

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?

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!

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

• 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 (e.g. Kafka, Iceberg, Trino, Flink, Snowflake)

• Mastery 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 Splunk, Grafana (other tools like New Relic, Datadog and Kibana 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, 2022 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.

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