Data Engineer

Job : Unstructured Data Engineer

Location: Remote

Duration: 6+ Months

An Unstructured Data Engineer is responsible for moving and transforming unstructured data such as documents, images, logs, XML files, and JSON files from legacy or current systems into new archival or data management platforms. This role often overlaps with data engineering, archival solutions, and data migration expertise.

Responsibilities

• • Extract unstructured datasets from legacy applications, databases, or file systems and transform them into formats suitable for archival or analysis

• • Design and implement data migration pipelines that handle structured and unstructured data while ensuring integrity and consistency

• • Support migration of historical data from legacy archival platforms to modern archival or cloud based storage solutions

• • Work with schema on read formats including XML and JSON to map data to internal standard schemas and integrate into data processing workflows

• • Perform data validation and reconciliation between source and target systems to ensure accuracy

• • Collaborate with workflow systems for data retrieval, approval, and archival processes

• • Maintain technical documentation for migration processes and workflows

• • Work with architects, quality assurance, reporting, and business teams to align migration with technical and business goals

Qualifications

• • Strong data engineering and ETL experience with a focus on large scale data migration

• • Proficiency in SQL and relational databases including Oracle, SQL Server, PostgreSQL, and MySQL

• • Experience with unstructured data formats including XML and JSON and schema mapping

• • Familiarity with archival or secondary storage platforms and cloud storage environments

• • Knowledge of graph theory and graph databases for complex data relationships

• • Programming skills in Java or Python for data processing and pipeline development

• • Experience using version control and collaboration tools

• • Five to eight years of experience in data engineering, database technologies, or related fields

• Tools and Technologies:

• • SQL

• • Oracle

• • SQL Server

• • PostgreSQL

• • MySQL

• • XML

• • JSON

• • Cloud storage platforms

• • Archival and secondary storage solutions

• • Java

• • Python

• • Version control tools

• • Workflow and collaboration platforms