Data Platform Engineer: Cloud SaaS & Big Data

Qualys, Inc.

United States

Remote

USD 130,000 - 200,000

Full time

9 days ago

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Job summary

Qualys, Inc. is seeking a Software Engineer to join its next-generation data platform and middleware.

You will prototype, design, develop and support a highly scalable SaaS-based cloud security data platform, working with a team of engineers to process hundreds of millions of transactions and terabytes of data daily. You will build microservices, review architectures, apply cutting-edge technologies, and contribute back to open-source as needed.

Qualifications

BS/MS degree in Computer Engineering, Computer Science, Applied Math or related field.
2+ years hands-on experience with developing SaaS based software products and solutions for service-oriented deployments in public (AWS, GCP, Azure, OCI, etc.) or private clouds.
Strong in data structures and algorithms.
Strong analytical and debugging skills.
Data-driven critical thinking problem-solving
Ability to clearly articulate and communicate technical concepts within and across teams.
Prior experience w orking with/ using any kind of distributed data systems like Redis, Kafka, Elasticsearch , Cassandra, Spark, Hadoop big data sy s tem, Apache flink stream processing , OLAP systems like Clickhouse .
Demonstrated passion for innovation with an ability to work within agile software development methodologies
Experience with infrastructure orchestration and automation tools (Terraform)
Hands-on experience using CI/CD pipelines
Java programming skills including object-oriented design, prototyping, development, testing, profiling, etc.
Foundation k nowledge of JVM concepts like garbage collection, heap, stack, profiling, class loading, etc.
Knowledge of the below is a plus
Deep u nderstanding of Distributed Systems concepts
Experience with applying data encryption and data security standards.
Experience with container and orchestration technologies such as Docker, Kubernetes etc.
Experience with monitoring tools such as Graphite, Grafana and Prometheus.
Experience with HashiCorp technologies such as Consul, Vault, Terraform and Vagrant.
Experience with configuration management tools such as Chef, Puppet or Ansible.
In-depth experience with continuous integration and continuous deployment pipelines.
Exposure to Maven, Ant or Gradle for builds.

Responsibilities

Engineer services handling data stored with millions of transactions per second, scaling to 100s of terabytes of data.
Review the application architecture and identify the data scale needs; investigate cutting-edge technologies and run POCs for production rollout.
Be the face and developer advocate of the stack you own and contribute back to open-source community if enhancements are needed.
Instrument both day 1 and day 2 operations on data technologies keeping high throughput and availability.
Deliver resilient client SDKs to applications to communicate with the data source you are responsible for.
Continue to seek better solutions to resolve scaling, availability and cost-efficiency.
Co-develop the big-data platform with ownership mindset to meet processing demands.