Job Description

Key Responsibilities1. Data Architecture & Pipeline Ownership

Design, architect, and maintain scalable, high-performance ETL/ELT pipelines supporting analytics, reporting, and data products.
Own and optimize complex SQL transformations across large-scale structured and semi-structured datasets.
Lead improvements in data infrastructure performance, reliability, and scalability across platforms (e.g., Oracle, PostgreSQL, BigQuery, Snowflake).
Drive the evolution and optimization of the Customer Data Platform (CDP) to support advanced business use cases and personalization.
Establish and enforce best practices for data quality, lineage, governance, and documentation.

2. Automation & Scalable Data Infrastructure

Design and implement automated, production-grade data pipelines and reporting workflows.
Build reusable, scalable data models and curated data layers to enable analytics at scale.
Lead automation initiatives to eliminate manual processes and improve operational efficiency.
Oversee deployment and performance of BI dashboards and reporting systems.

3. Data Products & Self-Service Enablement

Lead the development of internal and external data products, ensuring high data accuracy, security, and usability.
Build and enhance self-service data platforms to empower business teams with reliable and accessible data.
Contribute to data monetization strategies by delivering scalable and secure data solutions.

4. Technical Leadership & Cross-Functional Collaboration

Act as the technical lead in translating business requirements into scalable data architecture and solutions.
Mentor junior data engineers and guide best practices in coding, data modeling, and pipeline design.
Collaborate closely with business analysts, product teams, and IT to solve complex data challenges.
Provide advanced technical support for deep-dive analytics and high-impact business initiatives.

Required QualificationsTechnical Skills

Advanced proficiency in SQL, with strong experience handling large, complex datasets.
Solid experience designing and maintaining ETL/ELT pipelines in modern data stack environments.
Strong programming skills in Python (preferred) or R for data processing and automation.
Hands-on experience with cloud data platforms (BigQuery, Snowflake, Redshift) and relational databases (Oracle, PostgreSQL).
Experience with BI tools (Power BI, Tableau, Looker) and scalable reporting solutions.
Strong understanding of data modeling techniques (Star Schema, Data Vault, or similar).
Familiarity with data orchestration tools (e.g., Airflow, dbt) is a strong advantage.

Soft & Professional Skills

Strong ownership mindset with the ability to lead end-to-end data solutions.
Excellent problem-solving skills with a focus on scalability, performance, and data quality.
Ability to bridge technical and business perspectives effectively.
Comfortable working in a fast-paced retail and customer data environment.

Background & Experience

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related fields.
Minimum 4 years of experience in data engineering or similar technical roles.
Proven track record of building scalable data pipelines and data platforms.
Experience in retail, e-commerce, or customer/loyalty data is a strong plus.
Fluency in English and Vietnamese.