[Remote] Data QA Engineer at Mineral

Porto, Porto District, Portugal

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, DataIndustries

Requirements

Quality first mindset
Proactive mindset and approach to self-learning and continuous improvement
Experience of coaching others in quality engineering practices, behaviours and WoW
Strong background in Quality Engineering techniques with Agile methodologies
Working experience with SQL (Snowflake/DBT would be a bonus)
Good knowledge of Continuous Integration, Delivery and deployment through CI Pipelines
Working knowledge and experience of serverless concepts and technologies
Understanding of programming principles and best practice (e.g. DRY, SOLID for creating re-usable code)
Enthusiasm for Data Engineering and Data Science
Commercial background in Data Engineering or Science (desirable)
AWS services (Lambda, API Gateway, SFTP) (desirable)
Experience with non-functional testing (SQL profiling, Security and Access Control) (desirable)
Demonstrable knowledge of Data Quality Principles (DAMA) (desirable)
Knowledge of python as a programming language (desirable)

Responsibilities

Coach and mentor crews in relation to data quality engineering practices, behaviours and ways of working
Utilise toolsets that fit with the products under test and for use within a Continuous Integration and Deployment pipeline
Continually seek to advance the software quality practices and raise the overall maturity within the tribe, by identifying potential impediments / obstacles, which could impact upon achieving successful high-quality deliverables at pace
Collaboratively design, implement and execute automated test scenarios alongside engineers which demonstrate the business condition/behaviour under test and the expected results
Work closely with PO’s, Solution Architects, Principal QEs and Engineers to help design and implement testable solutions
Work collaboratively with the Engineering team to ensure that quality is built into everything, focusing on bug prevention over detection
Help innovate and deliver continuous improvements across the domains and through the Quality Engineering Chapter

Skills

SQL

Snowflake

DBT

CI/CD

CI Pipelines

Serverless

AWS Lambda

API Gateway

SFTP

Agile

Quality Engineering

Data Engineering

Mineral

Develops AI tools for sustainable agriculture

About Mineral

Mineral.ai develops technology solutions aimed at improving the agriculture industry. The company utilizes perception technology, artificial intelligence (AI), and machine learning (ML) to create tools that help farmers, researchers, and agricultural advisors increase crop yields, manage pests, and adapt to climate change. Their products include precision agriculture tools that optimize resource use and advanced data analytics platforms that provide insights from agricultural data. Unlike many competitors, Mineral.ai focuses on creating partnerships within the agriculture sector to co-develop solutions, enhancing their product offerings. The goal of Mineral.ai is to support sustainable food production and help feed the world more efficiently.

Mountain View, CaliforniaHeadquarters

N/AYear Founded

VENTURE_UNKNOWNCompany Stage

Food & Agriculture, AI & Machine LearningIndustries

51-200Employees

Risks

Transition from Alphabet may lead to financial instability and resource loss.

Licensing model could reduce control over technology application and revenue stability.

Difficulty in monetizing technology indicates challenges in creating durable revenue streams.

Differentiation

Mineral.ai uses AI and ML to revolutionize agriculture with precision tools.

The company partners with industry leaders like Driscoll's for real-world technology applications.

Mineral.ai's licensing model allows broad integration into existing agribusiness systems.

Upsides

Licensing model increases market reach and technology integration in agribusiness.

Partnerships with companies like Driscoll's enhance technology application and sustainability goals.

Growing interest in agrivoltaic systems offers new partnership opportunities for Mineral.ai.

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