AI Data Engineer

Experteer Overview In this role you will design and maintain data infrastructure to power AI models, collaborating with data scientists, ML engineers, and software teams to deliver reliable, scalable data pipelines. You will ensure data quality, governance, and performance across systems for AI workflows. The position offers impact through enabling model training, validation, and inference at scale. This is an opportunity to shape data architecture in a cross-functional, AI-driven environment. Compensation / Benefits * Design, build, and maintain data pipelines for AI and ML workflows * Collect, clean, and preprocess structured and unstructured data * Develop and manage datasets for model training, validation, and inference * Collaborate with ML engineers and data scientists to support model development * Ensure data quality, integrity, and availability across systems * Optimize data storage and retrieval for performance and scalability * Implement data governance, security, and compliance best practices * Monitor and troubleshoot data pipeline issues Tasks * Bachelors degree in Computer Science, Data Engineering, Information Systems, or related field (or equivalent experience) * Strong programming skills in Python and/or SQL * Understanding of ETL/ELT, data modeling, data warehousing * Familiarity with machine learning workflows and data requirements * Experience with data processing tools (e.g., Pandas, Spark) * Knowledge of relational and non-relational databases * Basic understanding of cloud platforms (AWS, Azure, or Google Cloud) Key requirements *

Monitor best practices * Monitor and troubleshoot data pipeline issues Tasks * Bachelors degree in Computer Science, Data Engineering, Information Systems, or related field (or equivalent experience) * Strong programming skills in Python and/or SQL * Understanding of ETL/ELT, data modeling, data warehousing * Familiarity with machine learning workflows and data requirements * Experience with data processing tools (e.g., Pandas, Spark) * Knowledge of relational and non-relational databases * Basic understanding of cloud platforms (AWS, Azure, or Google Cloud) Key requirements *