DataOps Engineer
Do you want to do impactful work that will be deployed to millions of citizens weekly? Do you want your input to be heard and taken into consideration? Apply and create a digital future with us!

100% REMOTELY

Salary up to $90,000 per annum, depending on experience - but please apply even if your financial expectations are a bit higher

Equity in the company

35 days of paid leave + 2 weeks of sick pay

B2B long-term permanent contract

Gibraltar-based fintech startup specialized in providing Bitcoin’s accessibility
We’re looking for DataOps Engineer for an international fintech startup on a mission to protect and grow its clients’ life savings. The company was founded to address two of the biggest issues with Bitcoin adoption: accessibility and security. In a matter of years, they developed an industry-leading platform that introduced cryptocurrency into the daily lives of millions worldwide.
Requirements

Significant hands-on experience with automating cloud data infrastructures and with best practices such as infrastructure as code, version control, collaboration, compliance, CI/CD tooling

Experience deploying robust container-based solutions in production environments

Strong Python knowledge, scripting languages and pipeline automation tools

Expertise with Relational Databases

Work experience with Google Cloud Platform Cloud Operations, IAM, BigQuery, Dataflow, TensorFlow etc.

Experience building auto-scaling systems.

Strong analytical and communication skills.
Nice to have

GitOps expertise

Experience with Kubernetes
Responsibilities

Contribute to building the data environment by focusing on the reliability, operationality and automation of the data infrastructure - we’re using Google Cloud Platform and we’re fans of the GitOps approach.

Work with data scientists and data engineers to make sure that data is properly managed throughout the analytics process and to ensure an iterative approach to data development supported by consistent testing and monitoring.

Establish scalable, efficient, and automated processes for large scale deployments (including machine learning solutions).

Manage, monitor, and troubleshoot data pipelines and machine learning infrastructure.

Ensure environments maintain the highest level of quality, security, scalability, availability and compliance amidst an environment of rapid change and growth.
Please include GDPR consent
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