Hire an Data Engineer
Engineers who build and maintain the data infrastructure that powers AI and analytics systems. They design data pipelines, warehouses, and ETL processes to ensure clean, reliable data for ML models.
Core skills
Every Data Engineer on the AI10 platform is vetted for these essential competencies.
Pricing
Transparent, affordable pricing for top AI talent.
Starting from
$10/hr
- Vetted and tested professionals
- Flexible hourly or project-based
- 48-hour talent matching
- Dedicated project management
- Replacement guarantee
Frequently asked questions
Why do I need a Data Engineer for AI projects?
AI models are only as good as their data. Data Engineers build the pipelines that collect, clean, transform, and deliver data to ML systems. Without reliable data infrastructure, even the best models produce unreliable results. Data engineering is typically 60-70% of AI project effort.
What data infrastructure can your engineers build?
ETL/ELT pipelines, data warehouses (Snowflake, BigQuery, Redshift), real-time streaming (Kafka, Kinesis), data lakes, feature stores, and data quality monitoring systems. They design infrastructure that scales with your data volume and AI ambitions.
Can Data Engineers work with messy, unstructured data?
Yes. Our engineers handle CSV files, API integrations, database migrations, PDF extraction, web scraping, and IoT sensor data. They build robust pipelines with data validation, error handling, and quality checks at every stage.
How do Data Engineers support ongoing ML operations?
They build automated feature pipelines that continuously transform raw data into ML-ready features, implement data drift monitoring, and ensure training and serving data consistency — the backbone of reliable ML in production.