Design and implement data migration and data preparation processes for structured
and unstructured data sources.
Develop Python-based data transformation and preparation routines for large and
complex datasets.
Process and manipulate natural-language data, converting unstructured or semi-
structured content into structured representations.
Design and implement JSON transformation, parsing, validation, and manipulation
routines.
Develop data cleansing, normalization, enrichment, validation, and transformation
processes.
Prepare JSON datasets and data structures required for Neo4j graph ingestion.
Define data mappings and transformation rules from source systems to target graph
structures.
Work with Neo4j engineers to ensure prepared data meets the requirements for
downstream ETL and graph ingestion.




Support the definition of data models, entities, relationships, attributes, and associated
transformation logic.
Identify data quality issues and implement appropriate validation and remediation
routines.
Optimize Python-based data preparation processes for performance, scalability, and
maintainability.
Document data flows, transformation logic, mapping specifications, and data preparation
procedures.
Collaborate with data engineers, Neo4j engineers, architects, and business stakeholders to
resolve data and integration challenges.
Support testing, reconciliation, and validation of migrated and transformed data.

📌 Data Architect (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India