About Us

Legacy Data Conversion specializes in transforming legacy and unstructured data into clean, structured, database-ready information. We work with enterprise clients across industries, converting data from PDFs, scanned documents, Excel files, text files, images, and legacy systems into modern formats with exceptional accuracy.

We are looking for a Data Engineer who enjoys solving complex data challenges and building reliable, scalable data processing solutions.

Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines.
- Extract, transform, and load data from multiple sources including PDFs, Excel, CSV, text files, APIs, and databases.
- Develop automated data extraction and validation workflows.
- Ensure high data quality, consistency, and integrity.
- Optimize data processing for large-scale datasets.
- Work with structured and unstructured data.
- Collaborate with software engineers and business stakeholders to understand data requirements.
- Create and maintain technical documentation.
- Troubleshoot and improve existing data processing systems.




- Implement data validation, monitoring, and error-handling processes.

Required Skills
- 2+ years of experience as a Data Engineer or similar role.
- Strong SQL skills.
- Proficiency in Python.
- Experience with ETL processes and data transformation.
- Experience working with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
- Knowledge of Pandas and data processing libraries.
- Familiarity with Git.
- Robust analytical and problem-solving skills.
- Excellent communication skills.

Preferred Qualifications
- Experience with OCR technologies.
- Experience processing PDF and scanned document data.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
- Experience with Docker.
- Familiarity with Apache Spark or similar big data technologies.
- Experience with workflow orchestration tools such as Airflow.

What We Offer
- Competitive salary.
- Fully remote work e

📌 Data Scientist (India)
🏢 Legacy Data Conversion
📍 India