Platform Engineer - Analytics Platform
Platform Engineer - Analytics Platform
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
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 platforms 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 () an initiative which started with this team as well our Snowflakebased 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. Were now starting off the migration to an orchestrated solution (K8sbased) and we need help to achieve this!
How we work
We operate on a strong belief in automation programmatic implementation and reusable design. Were 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 worldwide. 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 highavailability assessing and reducing engineering load and devising more effective ways for the team to look after its cloudbased 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. Were 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 crossfunctional teams including Analytics Experience and Data Governance to ensure alignment in data serving and consumption patterns.
Help establish and maintain highstandard 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 selfservice tooling within the organisation that helps engineers analysts or data scientists do their job more efficiently
Interested Find out more:
What do we offer:
Starting salary:RSU
#LIAB3 #LIHybrid
Additional Information :
For everyone everywhere. Were people building money without borders without judgement or prejudice too. We believe teams are strongest when they are diverse equitable and inclusive.
Were 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 its like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
