About the role
As an AI Data Engineer at TheWebVale, you will build data pipelines that extract, sanitize, and structure raw business content for machine learning and AI systems. You will process catalogues, legal contracts, clinic records, and educational media into clean training and evaluation sets.
You will collaborate with machine learning engineers and backend architects during our two-to-three week release cadences. You will ensure data pipelines are automated, resilient, and fully compliant with data privacy protocols.
What you will do
- Build automated data extraction pipelines to ingest text, PDFs, tables, and images.
- Develop sanitization scripts to strip personal identification data and unwanted noise.
- Structure raw data into clean JSONL, Parquet, and relational formats for AI models.
- Validate dataset integrity, schema consistency, and character encodings at scale.
- Implement automated schedule triggers and error notifications for ETL data jobs.
- Collaborate with AI engineers to curate balanced datasets for model evaluation.
What you will need
- Possess 2–4 years of professional experience in data engineering or AI data preparation.
- Demonstrate high proficiency in Python, Pandas, regular expressions, and SQL.
- Show practical experience parsing messy documents including PDFs, DOCX, and scanned forms.
- Understand data privacy principles, pseudonymization, and secure data handling.
- Possess disciplined habits with Git version control and automated script scheduling.
- Communicate data limitations, anomalies, and pipeline statuses clearly to teammates.
Nice to have
- Experience with distributed data tools like Apache Spark or DuckDB.
- Familiarity with OCR engines like Tesseract or AWS Textract.
- Knowledge of cloud object storage and data lake organization.