Senior Data Analyst

Role & responsibilities

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

1. Data Validation: Validate data across all the layers(bronze, silver,etc) in Databricks for completeness, structure and availability of required fields
2. DQ Rule Migration & BUILD: Select and build a set of existing DQ rules in Databricks as part of the PoC
3. PoC Testing & Reconciliation: Execute the rules in Databricks and compare results with the existing DQ results, investigating and resolving differences
4. 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
5. 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
6. DQ Reporting: Support the development of DQ outputs, KPIs and dashboard reporting from Databricks, including validation of report results
7. 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
• Good 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

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