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Automation Testing Engineer
D01 Marina, Raffles Place, People's Park, Cecil, Singapore
ContractInformation TechnologyJob Description
Experience Requirements Total QA/Testing Experience: 5+ years. Data Testing Experience: 3+ years specifically in Big Data, Hadoop, or CloudData Warehouse environments. Good to have : Databricks Experience: 1+ years of experience testing pipelines within a Databricks environment. Automation Focus: Proven track record of moving from manual SQL checks to automated Python-based testing frameworks. Migration automation testexperience using Python
Required Certifications Good to have: Databricks Certified Data Engineer Associate (at minimum). Preferred: ISTQB Foundation or Advanced Level (Test Automation Engineer).
Core Technical Skills
- Data Validation Frameworks Great Expectations / Pandera: Proficiency in using Python-based libraries to define data contracts and automated validation suites. DLT Expectations: Deep understanding of Delta Live Tables (DLT) expectations (Fail, Drop, Quarantining bad records). Advanced SQL: Expert-level SQL for complex data reconciliation, identifying duplicates, and null-value analysis across billions of records.
- Python for QA (PySpark) Pytest-Spark: Experience using pytest to write unit tests for PySpark transformations and logic. Notebook Testing: Ability to write automated test notebooks that validate Medallion Architecture transitions (Bronze to Silver, Silver to Gold). Data Reconciliation: Building Python scripts to perform source-to-target counts and checksums across distributed file systems.
- Performance Integration Testing Scalability Testing: Ability to validate that data pipelines meet performance SLAs when data volume spikes. End-to-End Orchestration Testing: Testing the reliability of Databricks Workflows and handling of job failures/retries. Schema Evolution: Testing how pipelines handle upstream schema changes without breaking downstream Gold tables.
- Governance Security Testing Unity Catalog Validation: Testing Row-Level Security (RLS) and Column-Level Masking to ensure unauthorized users cannot see sensitive data. Data Lineage: Validating that data lineage in Unity Catalog correctly reflects the movement of data across the Lakehouse.
EANumber: 11C4879 Reg. ID : R26161692
About Apar Technologies Pte. Ltd.
First seen: August 20, 2026
Last updated: September 19, 2026