AI Data Engineer Mid · Full-time · Remote →

Thewebvale; India; Remote; INR 800,000 - 1,500,000; Full time

Benefits offered by this job

Remote-first

Bhopal studio for hybrid days

Public portfolio

Job summary

TheWebVale is seeking an AI Data Engineer to build data ingestion pipelines and dataset validation routines for client AI models. You will extract, sanitize, and structure raw business content into clean training and evaluation sets, collaborating with ML engineers and backend architects.

You will work on Python-based ETL pipelines, handling PDFs, DOCX, and other documents, while ensuring privacy, schema consistency, and scalable automation across release cadences.

Qualifications

• 2–4 years of professional experience in data engineering or AI data preparation.
• Proficiency in Python, Pandas, regular expressions, and SQL.
• Experience parsing messy documents including PDFs, DOCX, and scanned forms.
• Understanding data privacy principles, pseudonymization, and secure data handling.
• Disciplined Git usage and automated script scheduling.

Responsibilities

• Build automated data extraction pipelines to ingest text, PDFs, tables, and images.
• Develop sanitization scripts to strip personal identification data and noise.
• Structure raw data into 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.

Skills

Python

Pandas

SQL

ETL

Regex

Tools

Docker

Git

Job description

You will build data ingestion pipelines, document cleaners, and dataset validation routines to fuel client artificial intelligence models.

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.

Python

SQL

ETL

Docker

Git

03 Responsibilities

• 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.

04 Requirements

• 01 / 06 Possess 2-4 years of professional experience in data engineering or AI data preparation.
• 02 / 06 Demonstrate high proficiency in Python, Pandas, regular expressions, and SQL.
• 03 / 06 Show practical experience parsing messy documents including PDFs, DOCX, and scanned forms.
• 04 / 06 Understand data privacy principles, pseudonymization, and secure data handling.
• 05 / 06 Possess disciplined habits with Git version control and automated script scheduling.
• 06 / 06 Communicate data limitations, anomalies, and pipeline statuses clearly to teammates.

What you get.

thewebvale.

• Remote-first, with a Bhopal studio for hybrid days
• Real client products across many industries
• Direct work with the founder and senior team
• Learning and tooling support
• Your work featured in our public portfolio

06 How we hire

Three steps, no tricks.

• Intro chat: A short call about what you want to work on and how you like to work.
• Work review: Walk us through projects, code or designs you are proud of.
• Paid task: A small paid task or pairing session, so both sides see the fit.