Work Expert (WE) is an independent publishing and referral website. We are not a recruiter, hiring manager, agent or employer, and we are not affiliated with or endorsed by micro1. Applying takes you to the platform's own website, where we may be recorded as the referring source. We may receive a referral fee at no additional cost to you. Read our full affiliate disclosure →
About the Role
The Role We are looking for a skilled Data Engineer with strong analytical thinking and experience building scalable data pipelines, performing exploratory data analysis, and working with both structured and unstructured data. In this role, you will help transform raw information into reliable, high-quality datasets that support research, analytics, and AI/ML model development. Exposure to machine-learning tools and AI technologies is highly valuable.
What You'll Do
Design, develop, and maintain scalable ETL pipelines.
Collect, clean, transform, and organize structured and unstructured data.
Conduct exploratory data analysis to identify trends, patterns, anomalies, and data-quality issues.
Collaborate with researchers, data scientists, and engineering teams to prepare datasets for AI and machine-learning initiatives.
Develop and maintain data models, database schemas, and data-storage solutions.
Write and optimize SQL queries for data extraction, transformation, and analysis.
Engaged directly through micro1. Apply via the link below - micro1 handles onboarding and payment.
Common Questions
micro1 has a reliability rating of reliable based on the listings we track, with an onboarding time of 1-3 days. See our full micro1 review for the details behind that rating.
Applying takes you to micro1's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.
$4-$5/h - Engaged directly through micro1. Apply via the link below - micro1 handles onboarding and payment.
Design, develop, and maintain scalable ETL pipelines. Collect, clean, transform, and organize structured and unstructured data. Conduct exploratory data analysis to identify trends, patterns, anomalies, and data-quality issues.