About Opensee
Opensee provides instant big data analytics solutions to financial institutions. Our mission is to empower business users to autonomously exploit data at a scale and granularity never seen before in order to optimize risk management, trade execution, regulatory reporting and more.
Founded in 2015 by senior banking executives and big data technology experts, Opensee's commercial traction exploded in 2020 with deployment in several Tier 1 financial institutions on critical use cases. To sustain that growth, we doubled our headcount that same year and are now expanding in London, NYC and Singapore.
What’s in it for you?
Develop expertise in one of the most advanced solution for risk aggregations
Work in a dynamic environment where innovation and creativity are highly value
Benefit from a wealth of development opportunities as we constantly seek new talents to join us, and support our growth
Missions
What are you going to do?
You will work in the team responsible for all aspects of client implementation and support including production environments for critical use cases . This involves closely working with the client’s IT and Change teams to drive growth and address concerns efficiently:
Deploy the Opensee solution on client infrastructure at different stages of the sales process (POC / Implementation / Production). Client infrastructure includes bare metal environments, VM and cloud deployment (AWS, AZURE, Google Cloud Platform). As a DataOps Engineer you will master the deployment framework of Opensee using the in-house CLI tool for deployment on bare metal or inside k8s on cloud. You will also be able to deploy the Opensee SaaS platform available on Google Cloud.
Integrate our solution within the client environment, including:
Advise the client on how to integrate Opensee to customer data processes/flows, perform troubleshooting, and fine tune the ingestion of data
Advise the client on best practice for using the platform in an efficient manner, troubleshooting of the platform and fine tuning performance on the data visualisation side
As a Data Ops Engineer, you are a key part of the client implementation success on the technical side, with the overall goal to enable the client IT team to take ownership of the deployment process and all ops related tasks for the platform. For example
high availability setup
resiliency setup
disaster recovery management
infrastructure configuration and troubleshooting
troubleshooting any issue encountered on the list above, the infrastructure, network, services failure, replication system issues, data corruption, API or SQL query performances
Advising the client on best practices, and fine tuning the performance of the platform on both writing and reading side
Support the clients on a daily baisis
Keywords: linux, bash, python pandas, ops, devops, BigData, database, docker, kubernetes, AWS, AZURE, GCP, Cloud
Profil
About you
Interest: If you like to get your hands dirty from system to database internal behaviour passing by firewalls and ssh tunnels on multiple environments, come and talk to us!
Qualities: Great communication skills; Autonomy AND team work; Creativity, Problem-solving mindset, Proactivity, Troubleshooting
Prior experience: Minimum 2 years as an Integration, Implementation or Support Engineer, Ops / DevOps experience (on-premise or in cloud) a plus.
Technical skills:
Unix systems / Bash / networks
Terraform / golang / Docker / Kubernetes
Big data / Distributed databases / SQL / Python (numpy, pandas)
Scripting / Analyzing / Optimizing in the context of Tera or Peta scale data
Testing, Deployment logics, Hardware specifications, Integration
Language skills: Fluent in English both written and verbal, French is a plus
Working conditions
Permanent position
Location : London (the City)
This is a hybrid role with 3 days a week in central London and 2 days working from home
To apply for this role you must have the right to work in the UK as Opensee do not currently sponsor visa applications
How to apply
Send us your resume and a brief description of why you are interested in joining us, and we will come back to you very shortly!