Strong data modelling across conceptual, logical, and physical layers with clear artefacts (ER models, graph schemas, JSON / Avro / DDL)
Hands-on experience with SQL and PL / SQL for reading / refactoring stored procedures and writing performant queries
Practical experience with AWS services, including RDS, S3, Lambda, IAM / Secrets Manager, CloudWatch / CloudTrail, and Amazon Neptune.
Proficiency in Python for data engineering, validation, profiling, and reconciliation tasks; Groovy for scripting and pipeline integration (e.g., GitHub actions)
Experience with manifest-driven mapping or schema registry patterns; ability to govern schema changes and versioning
Understanding of IAM models (RBAC / ABAC), PII handling, and audit / lineage requirements in regulated environments