AI Data Architect / Senior Data Engineer

Design production-grade enterprise connectors and ETL/ELT pipelines for both structured enterprise systems such as ERP, CRM, OSS/BSS, billing, finance, HR, and unstructured sources such as emails, documents, logs, transcripts, and media files. • Build ingestion and transformation pipelines using Python, SQL, PySpark, Apache Spark, Airflow, dbt, Dagster, Flink, or equivalent technologies. • Create frameworks for data labelling, contextualization, harmonization, enrichment, and classification workflows to configure AI agents. • Architect integration with knowledge graphs and vector databases for hybrid search, semantic retrieval, contextual reasoning, and AI-ready data access. • Build and maintain Ontology/knowledge graph pipelines using Neo4j, RDF/OWL, Apache Jena, Stardog, GraphDB, or equivalent technologies. • Implement graph validation frameworks such as SHACL or ShEx to programmatically enforce data integrity rules over enterprise knowledge graphs. • Implement data quality automation using frameworks such as Great Expectations, AWS Glue DataBrew, dbt tests, custom validation pipelines, or equivalent tools.