Data Engineer

• Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to process and integrate data from multiple sources, ensuring high-quality and reliable data flow.
• Database Management: Manage and optimize relational and non-relational databases including MongoDB, HubSpot, Stripe, ensuring data accessibility and integrity for the data science and analytics teams.
• ETL Process: Develop and implement ETL (Extract, Transform, Load) processes using Databricks to transform raw data into usable formats for analysis and reporting.
• rETL Process: Implement and manage reverse ETL processes using tools such as Hightouch to build data models, create audiences, sync audiences back to operational tools.
• Data Quality & Monitoring: Ensure the quality and accuracy of data by conducting regular checks, resolving data inconsistencies, and optimizing data workflows.
• Collaboration with Data Teams: Work closely with data scientists, analysts, and product teams to understand data needs and deliver the infrastructure to support advanced analytics and machine learning models.
• Cloud Infrastructure: Utilize cloud platforms (e.g. AWS) for data storage and processing, ensuring scalability and security.
• Performance Optimization: Continuously monitor, optimize, and troubleshoot data pipelines for performance, reliability, and scalability.

Compensation & Benefits:

• Competitive salary with 13th-month pay and performance bonus.
• Quarterly performance bonuses and year-end awards.
• Paid sick leave, maternity leave, and vacation days.

Work Environment:

• Agile-Scrum methodology with flexible work hours.
• Talented people from all over Vietnam and the world.
• International team for global career growth.
• State-of-the-art equipment provided.
• Beautiful working environment near Danang's city center (Dragon Bridge) and Hanoi office.

Health & Wellness:

• PVI health care program & annual health checks.
• Sports clubs (football, badminton) & company retreats.
• Modern pantry for relaxation.

Professional Growth:

• Training, mentoring & e-learning opportunities.
• 1-2 performance reviews annually.
• Potential opportunities to join a fast-growing company.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience 4+ years in data engineering, with a strong understanding of data modeling, ETL processes, and database management.
• Proficiency in programming languages (e.g., Python, SQL, Scala) and frameworks (e.g., Apache Spark, Hadoop).
• Experience with cloud platforms (AWS) and their data-related services (e.g., Redshift, BigQuery, S3).
• Solid experience with data warehouses and platforms such as Databricks, as well as building data lakes.
• Strong understanding of data architecture principles and best practices for managing large datasets.
• Familiarity with version control systems (e.g., Git) and containerization technologies (e.g., Docker).

Nice to have:

• Experience with big data technologies (e.g., Hadoop, Spark).
• Familiarity with real-time data streaming tools (e.g., Apache Kafka).
• Experience working in the fitness or wellness industry, particularly with personal trainer/client management systems.