Data QA

Ambition; Hong Kong; On-site; HKD 480,000 - 900,000; Full time

Job summary

Ambition is seeking an experienced data testing and validation specialist in Hong Kong to ensure end-to-end data quality from ingestion to marketing data models. You will validate upstream and downstream data flows, assess schema changes, and verify ETL/ELT logic within a Databricks-based lakehouse. Collaboration with global teams is key.

Required are 5+ years in data engineering, analytics, or QA, with Databricks, Python, SQL, and a strong focus on manual data testing and data model validation.

Qualifications

• 5+ years minimum in a Data Engineering, Data Analyst, or data-focused QA role.
• Hands-on Databricks experience with Data Lake solutions and Medallion architecture.
• Strong Python scripting for data validation and advanced SQL for profiling.
• Solid understanding of ETL/ELT pipelines and dimensional modeling.
• Heavy emphasis on manual data testing, regression testing and data model validation.

Responsibilities

• End-to-end data testing and validation across the entire data pipeline.
• Validate multi-channel data flows into the Data Lake and SCV model.
• Analyze impact on data models and schema when adding new sources.
• Verify ETL/ELT logic and schema consistency across Medallion layers in Databricks.
• Collaborate with global delivery teams and stakeholders to ensure data accuracy for campaigns and CRM.

Skills

Databricks

Python scripting

SQL

Data validation

Regression testing

Data modeling

ETL/ELT pipelines

Cross-functional collaboration

Tools

Databricks

Medallion architecture (Bronze, Silver, Gold)

Data Lake solutions

Job description

End-to-End Data Testing & Validation: Conduct hands-on manual data testing and validation across the entire data pipeline-from raw channel ingestion to final marketing data models.

Upstream & Downstream Integration Testing: Validate multi-channel CRM, transaction, and behavioral data flowing into the Data Lake, ensuring the Single Customer View (SCV) model accurately feeds downstream MarTech platforms.

Data Model & Schema Impact Analysis: Introduce new multi-channel data sources (store apps, websites, e-commerce marketplaces, offline POS) while verifying that Medallion data models (Bronze, Silver, Gold) remain unimpacted.

Data Lake Pipeline Verification: Verify ETL/ELT logic, data transformations, and schema consistency across Medallion layers in a Databricks environment.

Cross-Functional Collaboration: Partner closely with global delivery teams (India/US/HK), data engineers, and marketing stakeholders to ensure data accuracy for campaign targeting and CRM execution.

Key Requirements

Experience: 5+ years minimum in a Data Engineering, Data Analyst, or Data-focused QA role.

Data Engineering Competency: Hands-on experience with Databricks, Data Lake solutions, and Medallion architecture (Bronze, Silver, Gold layers).

Technical Skills: Strong Python scripting for data validation/querying and advanced SQL skills for deep data profiling.

Data Pipeline Knowledge: Solid understanding of ETL/ELT pipelines, data integration, dimensional modeling, and schema relationships.

Testing Focus: Heavy experience in manual data testing, regression testing, and data model validation (over standard front-end or automated UI testing).

MarTech / CRM Domain: Prior exposure to customer data platforms, MarTech tools, CRM data, or e-commerce/retail transaction pipelines is a strong advantage.