QA Automation Engineer / Saas Products

5 - 7 years experience  •  Technology

Salary depends on experience
Posted on 06/29/18
Redwood City, CA
5 - 7 years experience
Technology
Salary depends on experience
Posted on 06/29/18

The Role
At Delphix, quality comes first, and our QA team is the guardian of that quality. QA works closely with project teams to define and execute test plans continually throughout  the development process. QA engineers at Delphix are well-versed in test automation - from automating routine tests to building a robust automation infrastructure for scale and reliability.
This role is part of a team focusing on transforming our business from an on-premise to a SaaS delivery model for our enterprise products. The ideal candidatewill have a passion for helping other members of our engineering organization work through challenges and strong empathy for others as they go through the learning curves involved.

Responsibilities

    • Help transform QA processes to an incremental, continuous testing and delivery model
    • Analyze functional requirement and project architectures to build test strategies, test plans, test cases and test schedules
    • Design, implement, maintain and execute test automation for a hybrid SaaS and on-prem product
    • Collaborate with product and engineering leaders on acceptance criteria
    • Collaborate with engineers to diagnose and troubleshoot failures in test environments
    • Proactively assess issues and risks and bring them to conclusion through effective collaboration and influence.
    • Manage and update bug workflows
    • Mentor team members as we transition from an on-prem product to a Hybrid Cloud datacenter product
    • Ensure quality in a CI/CD workflow.

Qualifications

    • 3+ years of coding experience
    • 4+ years of experience testing SaaS products
    • Experience with continuous integration and deployment environments and how to ensure quality within such environments

Here’s what we’re into. If you’re interested in these, come join us

    • Public clouds such as AWS, Azure and GCP
    • Writinginfrastructure as code
    • Build and deployment tooling such as Jenkins, Artifactory, GitLab, Serverless, and AWS Cloudformation
    • Product based feature flags and feature rollout strategies
    • Production environment metrics and monitoring systems such as NewRelic and DataDog
    • Logging systems such as ELK
    • Automation frameworks in Python such as  Selenium, Unittest
    • NoSQL such as AWS Dynamo and ElasticSearch
    • Traditional Database Technologies such as (RDS) Postgres
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