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Automation Testing Engineer

Automation Testing Engineer

apar technologies pte. ltd.
5-7 Years
SGD 4,000 - 7,500 per month
Early Applicant
  • Posted a month ago
  • Be among the first 10 applicants

Job 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.
AutomationFocus: 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
1. 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.
2. 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.
3. 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.
4. 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

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Key Skills

Pytest-Spark

Performance Integration Testing

Python for QA PySpark

Data Validation Frameworks

Governance Security Testing