Jul 2026 — Present
Opala current
Rules Engine QA: Coverage Requirements Discovery (CRD) workflow
Owns test design and automation for the rules engine behind the CRD workflow, working against real deployed Azure environments rather than mocks.
responsibilities
- Wrote the full test plan from scratch: scope, environments, test-data strategy, entry and exit criteria, risk register and coverage matrix.
- Catalogued 77 test cases across positive, negative, edge, fallback and functional tiers. Where specs were silent or out of date, I grounded cases in the source code.
- Ran black-box testing against VPN-gated environments with signed JWT authentication and tenant-scoped requests.
- Built a pytest regression suite parameterised by environment, with a shared HTTP client covering every endpoint in scope.
- Found and fixed two security defects in product code, verified against the full backend test suite with no regressions.
- Traced a reference-data quality issue to its source extract, quantified the impact and raised it as a tracked engineering decision.
- Built the Jira/Xray structure: test plan, test issues, per-environment executions, and a mapping from automated test IDs to Jira keys for result import.
Azure data engineering: Data Lake and Databricks
Built ingestion pipelines into Azure Data Lake Storage through raw/bronze, curated/silver and consumption/gold layers, with Databricks processing into Delta Lake.
responsibilities
- Landed raw data in ADLS with validation gates before each layer moved downstream.
- Cleaned, transformed and joined data in Databricks notebooks (PySpark and SQL), writing versioned Delta Lake tables.
- Ran data-quality checks for schema conformance, nulls and duplicates, and referential integrity against source.
- Handled sensitive data under least-privilege access, with column-level treatment of sensitive fields and audit-conscious processing.