Lead the development and ongoing management of the company's cloud-based data lake and common data platforms (CDP), ensuring they are scalable, secure, and optimized for business needs.
Oversee data ingestion processes from a variety of on-premise and cloud-based sources, utilizing batch and real-time methods for collecting and integrating data.
Utilize Azure Data Factory, Databricks, and other relevant tools to transform raw data according to business logic, ensuring it is stored and processed efficiently in multiple layers (bronze, silver, gold).
Implement and manage real-time data ingestion using Confluent Cloud (Kafka) and similar technologies to support business intelligence and decision-making.
Ensure data privacy protocols are followed by masking Personally Identifiable Information (PII) and safeguarding sensitive data throughout its lifecycle.
Set up and maintain CI/CD pipelines to automate data workflows using Azure DevOps, ensuring smooth and efficient deployments.
Continuously monitor and optimize ETL jobs, data pipelines, and cloud resources to improve system performance, minimize errors, and reduce costs.
Work closely with the data science team to prepare clean, stable, and high-quality data for AI/ML model development and other predictive analytics initiatives.
Lead the development of interactive Power BI dashboards and reports to deliver insights into business performance, sales behaviors, fraud detection, and more.
Establish efficient and secure methods for sharing data across teams using platforms like SharePoint and Databricks Unity Catalog.
Mentor junior data engineers, foster a collaborative team environment, and drive best practices in data engineering.

Bachelor’s degree in Information Technology, Computer Science, or a related field.
5+ years of experience in data engineering, with a focus on cloud platforms (preferably Azure) and data pipeline management.
5+ years of experience
Proficiency with Azure services, particularly Azure Data Factory, Azure Databricks, and other cloud-based data management tools.
Azure services
Extensive experience with real-time and batch data ingestion, transformation, and storage techniques (e.g., Delta Lake, Kafka, Flink).
Strong understanding of data privacy principles, including PII handling, data masking, and governance best practices.
Hands-on experience with tools such as IBM DataStage, Spark, PySpark, T-SQL, and Databricks for data transformation and integration.
Experience with Azure DevOps or similar tools to automate and streamline data processes.
Expertise in developing business intelligence dashboards and reports using Power BI.
Experience working alongside data science teams to prepare and optimize data for machine learning models.
Good command of English
Strong problem-solving abilities, excellent communication skills, and the ability to collaborate across teams.

13th-month salary
14+ annual leaves per year
Premium healthcare insurance, starting from your probation period
Project reviews and yearly performance appraisals
Annual company trips
Teambuilding activities: Team lunch/dinner, events, and celebrations, sports clubs (football, yoga, badminton, etc.)
International team with flexible working time + hybrid working
Tailor-made career path
Technical workshops and training courses
Mobility: Opportunities to be on-site abroad in our offices in over 60+ countries

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Hạn nộp hồ sơ: 11/04/2025

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