New Job Opening: Data Engineer (Data Masking project) in Hong Kong

Job Description

About our client

A major financial-services organisation is undertaking a large-scale data-privacy programme and is hiring a contract Data Engineer to build the data-masking pipelines behind it. You will join a small specialist delivery team, reporting to a senior data architect, and own the hands-on build that turns agreed masking rules into production-grade, de-identified data.

Responsibilities

• Design and build the extract–mask–load pipelines that de-identify high volumes of sensitive data across a data warehouse and its downstream data marts


• Apply the right technique to each data type — substitution, format- and checksum-preserving values, deterministic tokenisation, format-preserving encryption for payment-card fields, date-shifting, and redaction of free-text PII


• Stand up and maintain the tokenisation/consistency layer so masked values stay consistent and referential integrity holds across tables, marts and source systems


• Run masking jobs in waves across multiple database platforms, monitoring, tuning and reconciling outputs between runs


• Work with QA on validation and defect resolution, and document the pipelines and run procedures


• Operate entirely within the client’s secured environment under least-privilege access and full audit logging

Requirements

• Several years of hands-on data engineering, with strong SQL and a scripting language such as Python


• A track record of building ETL/data pipelines over large relational datasets (millions of rows) across more than one database engine (e.g. Oracle, SQL Server)


• Practical knowledge of data de-identification/masking techniques and how to preserve referential integrity


• Disciplined, deadline-driven delivery within controlled or regulated environments


• Hong Kong based and able to work on-site


• Fluent English; Cantonese and/or Mandarin an advantage

Preferred

• Hands-on experience with an enterprise masking or test-data management platform (e.g. Informatica, Delphix or similar)


• Exposure to banking/financial-services data and to data-protection standards such as PDPO or PCI DSS


• Familiarity with data warehouse / data mart and dimensional modelling