Position: Middle/Senior DevOps Engineer (GCP)
Company: Softserve
Experience required: 3y
Category: DevOps
English level: intermediate
Published: 2020-10-01T00:00:00+03:00

WE ARE

At SoftServe, we are advisors and providers who operate at the cutting-edge of technology. With you, we set goals and reach them to grow better together, learning from both successes and mistakes. We are a team of 8 000+ thinkers and makers in more than 30 offices worldwide, true professionals, and good people, who like what we do and do it well.  

We’re working with a top Real Estate agency on building a mobile application for thousands of agents. We communicate with Top experts in Real Estate business and help them expand their business.

YOU ARE

A mature DevOps Engineer with experience in

Cloud hosting providers such as GCP, AWS, Azure (GCP preferred)
Cloud orchestration and/or configuration management with Terraform
Creating and implementing containerization strategies using Docker
Microservice orchestration using Kubernetes
Continuous integration and delivery (CI/CD)
Supporting databases, including backup and recovery procedures, such as CloudSQL, BigQuery, MongoDB
At least one high-level programming language, such as Python (preferred), Ruby, Perl
Working and influencing across teams
Guiding the direction of one’s own teams
It would be a great plus point if you are

GCP-certified as Google Cloud Architect and/or Google Data Engineer
Having a deep understanding of ML training cycle, ML model storage & deployments
Experienced with IaC: Terraform (preferred), Cloudformation
Supporting databases, including data warehouse (DWH), such as CloudSQL, BigQuery, MongoDB, Oracle, AWS Redshift
Experienced with streaming and integration pipelines, such as Pub/Sub, Dataflow, DataFusion, Spark Experience with workflow orchestration, such as Composer, Apache Airflow, AWS Glue, Informatica(ETL)

YOU WANT TO WORK WITH

Provisioning of GCP cloud infrastructure
The data team (ML data scientists)
Configuration of CI/CD pipelines for ML workflows
Preparation and driving of the deployment of machine learning algorithms into production
Management of operation aspects (performance, uptime, reliability, and resilience) of business-critical data assets
Identifying improvements to infrastructure and operational procedures
Conducting internal training and coaching for the research team and software engineers on proper cloud usage

TOGETHER WE WILL

Support your technical and personal growth — we have a dedicated career plan for all roles in our company
Enjoy flexible working hours — whether you are a morning bird or a sleepy-head it is ok with us
Take part in internal and external events where you can build and promote your personal brand
Give you access to experienced specialists who are very willing to share their knowledge
Show you our casual atmosphere — no dress code
Care about your individual initiatives — we are open for them, just come and share your ideas
Share many other advantages with you such as attractive salary, modern office, a package of benefits, language classes