Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams, on-demand. With $100+ million in annual revenue and triple-digit growth, Toptal is the largest fully distributed workforce in the world.
We take the best elements of virtual teams and combine them with a support structure that encourages innovation, social interaction, and fun (see this video from The Huffington Post). We see no borders, move at a fast pace, and are never afraid to break the mold.
The Data Science team builds unique Machine Learning solutions to support Toptal with decision-making capabilities, in order to provide full support for a data-driven organization. Currently, we are looking for a Data Science QA Engineer to join this growing team.
By joining our team, you will get the opportunity to use your skills and experience to help us build and monitor our state-of-the-art Data Processing and Machine Learning services. You will be working with a team of highly skilled Data Scientists and Data Engineers from around the world. You will get to use cutting edge technologies every day, and you will play a major role in choosing the right solutions and in the development of new tools.
We don’t cut corners, and we don’t make compromises - we focus on high-quality solutions that bring value. We are remote-only, have no offices, and fully embrace a flexible work-life balance.
This is a remote position that can be done from anywhere. All communication and resumes must be submitted in English.
You will design, build, and maintain efficient, reusable, and reliable automated testing solutions. Being mindful of the test pyramid, you will identify and use the right approach and tools, ranging from manual testing to tailored solutions. In a continuous collaboration with your team members, you will improve techniques, tools, and QA processes, you will brainstorm ideas, and communicate your status and progress.
You will be reviewing the work of your colleagues, mentoring them, providing feedback, and continuously improving yourself. We need innovation, creativity, and solutions that will have a significant impact on our velocity. We, in turn, will give you autonomy and freedom to turn your ideas into reality.
In the first week you will:
- Onboard and integrate into Toptal.
- Rapidly begin learning about Toptal’s history, culture, and vision.
In the first month you will:
- Understand our team structure and workflow.
- Complete necessary trainings.
- Deliver your first tickets.
In the first three months you will:
- Get to know your team.
- Understand our analytics architecture.
- Start working on one or more projects.
- Propose technical and non-technical solutions and improvements.
- Begin helping with estimations related to the projects with which you’re involved.
- Begin collaborating with other departments.
In the first six months you will:
- Be completely familiar with the workflow and the team.
- Begin to be part of on-call rotation.
- Be fully integrated and a participant member of all workflow including planning sessions, reviews, and retrospectives.
In the first year you will:
- Be on top of most the analytics initiatives and projects.
- Participate in the hiring process of possible new team members.
- Act as a representative of the team through an initiative, being responsible for talking with stakeholders, creating tickets, and coordinating expectations.
- Establish a relationship with the product department and other stakeholders.
- Have 3+ years of Quality Assurance experience.
- Have 3+ years of experience in Python.
- Experience in building tailored QA solutions is a big plus.
- Experience with monitoring Data Pipelines and Machine Learning deployments/services is a plus, but not required.
- Being familiar with the Google Cloud ecosystem is a plus.
- Have a keen eye for detail and a commitment to excellence.
- Ability to solve complex problems by considering multiple solutions, weighing them, and deciding on the best course of action.
- Thrive on providing and receiving honest but always constructive feedback.
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