Mineral

Data Quality Engineer

Porto, Porto District, Portugal

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Data & AnalyticsIndustries

Requirements

Candidates should have 5+ years of experience in Data Engineering or Data Quality Engineering roles in fast-paced environments, a deep understanding of data flows, patterns, and common error sources in large-scale environments, experience with both proprietary and open-source big data technologies and platforms (Snowflake, Databricks, Vertica, Spark, Airflow) and open-source/3rd party data quality tools, a sound understanding of various cloud technologies, especially AWS, experience defining and crafting automated data quality monitoring/testing/alerting frameworks for data projects, strong communication and collaboration skills, and a proactive mindset with strong problem-solving instincts and a curiosity for root-cause analysis.

Responsibilities

The Data Quality Engineer will serve as the voice of data quality within the Data Engineering team, design and implement automated testing and alerting frameworks to monitor data pipelines, drive quality from data ingestion through to data presentation layers, collaborate with data engineers and stakeholders to ensure quality is built-in from the start, analyze complex datasets to identify inconsistencies, trends, and areas for improvement, enhance and maintain proprietary and standardized taxonomies, ensure performance and reliability across data systems and pipelines, promote and apply best practices for testing with data in mind across the broader engineering community, and proactively improve data systems and processes.

Skills

Data Quality

Data Engineering

Data Lakes

Data Warehousing

Data Migration

Data Verification

Big Data Technologies

Snowflake

Databricks

Vertica

Spark

Airflow

Open-source Data Quality Tools

AWS Cloud Technologies

Automated Testing

Monitoring and Alerting Frameworks

Root Cause Analysis

Data Ingestion

Data Analysis

Collaboration

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.

Key Metrics

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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