- Data Discovery: Identify the SAP tables and fields used for existing Data Quality(DQ) rules & reports and locate the corresponding data in Databricks

- Data Validation: Validate data across all the layers(bronze, silver,etc) in Databricks for completeness, structure and availability of required fields

- DQ Rule Migration &
- BUILD: Select and build a set of existing DQ rules in Databricks as part of the PoC

- PoC Testing &

- Reconciliation: Execute the rules in Databricks and compare results with the existing DQ results, investigating and resolving differences

- End-to-End Rule Migration: Following the PoC, migrate / BUILD the agreed As-Is DQ rules to data bricks, including SQL logic, data mappings, rule outputs and required transformations

- Data &

- Rule Validation: Perform end-to-end validation of source data, DQ rules, results and defects in Databricks to ensure the migrated process produces expected outcomes





- DQ Reporting: Support the development of DQ outputs, KPIs and dashboard reporting from Databricks, including validation of report results

- Documentation &

- BAU Handover: Document data mappings, DQ rules, validation results and migration processes

- SQL &

- Pyspark/Python knowledge

- Experience in Data Quality / Data Validation.

- Experience working with SAP data, preferably master data

- Valuable understanding of SAP tables

- Experience with Databricks platform
- Experience in data reconciliation and comparison between different data sources.

- Ability to translate DQ requirements/rules into technical SQL or Python logic

- Experience in DQ rule testing, defect analysis and troubleshooting

Degree Level

📌 Data Analyst (Bengaluru)
🏢 Diageo
📍 Bengaluru