SalaryPeak

Data Test Engineer

SHELL INFOTECH PTE. LTD.
Singapore 5+ years Posted Apr 21, 2026

Salary Range

SGD 84,000 - SGD 108,000 /year

SGD 7,000 - SGD 9,000/month

Skills Required

Performance TestingPySparkMandatory TestingBig DataData PipelineHadoopData EngineeringPythonData Warehouse ArchitectureData Validation

Job Description

  • Experience Requirements:
  • Must have QA/Testing Experience.
  • Data Testing Experience specifically in Big Data, Hadoop, or Cloud Data Warehouse environments.
  • Databricks Experience of testing pipelines within a Databricks environment.
  • Automation Focus: Proven track record of moving from manual SQL checks to automated Python-based testing frameworks.
  • Mandatory: 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.