At Zyte, we eat data for breakfast and you can eat your breakfast anywhere and work for Zyte. Founded in 2010, we are a globally distributed team of over 250 Zytans working from over 28 countries who are on a mission to enable our customers to extract the data they need to continue to innovate and grow their businesses. We believe that all businesses deserve a smooth pathway to data.
For more than a decade, Zyte has led the way in building powerful, easy-to-use tools to collect, format, and deliver web data, quickly, dependably, and at scale. And today, the data we extract helps thousands of organisations make smarter business decisions, secure competitive advantage, and drive sustainable growth. Today, over 3,000 companies and 1 million developers rely on our tools and services to get the data they need from the web.
About the Job:
QA is an important function within Zyte. The QA team works to ensure that the quality and usability of the data scraped by our web scrapers meets and exceeds the expectations of our enterprise clients.
Due to growing business and the need for ever more sophisticated QA, we are looking for a talented Data QA Engineer with both automated and manual test experience to join our team. You will take automated, semi-automated, and manual approaches and apply them in the verification and validation of data quality.
- Understand customer web scraping and data requirements; translate these into test approaches that include exploratory manual/visual testing and any additional automated tests deemed appropriate.
- Provide input to our existing test automation frameworks from points of view of test coverage, performance, etc.
- Ensure that project requirements are testable; work with project managers and/or clients to clarify ambiguities before QA begins.
- Take ownership of the end-to-end QA process in newly-started projects.
- Work under minimal supervision and collaborate effectively with Head of QA, Project Managers, and Developers to realize your QA deliverables.
- Draw conclusions about data quality by producing basic descriptive statistics, summaries, and visualisations.
- Proactively suggest and take ownership of improvements to QA processes and methodologies by employing other technologies and tools, including but not limited to: browser add-ons, Excel add-ons, UI-based test automation tools etc.
- BS degree in Computer Science, Engineering or equivalent.
- Demonstrable Python experience, minimum of 3 years (please provide code samples in your application, via a link to GitHub or other publicly-accessible service).
- Minimum 3 years in a Software Test, Software QA, or Software Development role, in Agile, fast-paced environment and projects.
- Solid grasp of web technologies and protocols (HTML, XPath, JSON, HTTP, CSS etc.); experience in developing tests against HTTP/REST APIs.
- Strong knowledge of software QA methodologies, tools, and processes.
- Ability to formulate basic to intermediate SQL queries; comfortable with at least one RDBMS and its utilities
- Excellent level of written and spoken English; confident communicator; able to communicate on both technical and non-technical levels with various stakeholders on all matters of QA
- Knowledge and experience of Scrapy and other Python-based scraping frameworks a distinct advantage.
- Prior experience in a Data QA role (where the focus was on verifying data quality, rather than testing application functionality).
- Interest in and flair for Data Science concepts as they pertain to data analysis and data validation (machine learning, inferential statistics etc.); if you have ideas, mention them in your application.
- Knowledge of and experience in other technologies that support a modern cloud-based software service (Linux, AWS, Docker, Spark, Kafka etc.)
As a new Zytan, you will:
Become part of a self-motivated, progressive, multi-cultural team.
Have the freedom and flexibility to work from where you do your best work.
Attend conferences and meet with team members from across the globe.
Work with cutting-edge open source technologies and tools.