Senior Data Engineer

Qualgo is more than just a tech company; we’re a movement to build a safer, more trustworthy digital Vietnam. We believe everyone deserves to connect, communicate, and transact online without fear. Our innovative platform, powered by AI and advanced security technologies, provides a secure cyberspace for Vietnamese individuals and businesses, empowering them to embrace the full potential of the digital age. We are deeply committed to supporting Vietnam’s national digital transformation.  Job SummaryAs a Senior Data Engineer, you will play a crucial role in designing, building, and maintaining the core data infrastructure that powers Qualgo’s products and data-driven initiatives. You will be responsible for developing scalable data pipelines, managing our data warehouse and data lake environments, and ensuring data quality and reliability. You will work closely with data scientists, analysts, software engineers, and product teams to understand their data needs and provide them with the necessary tools and infrastructure. This is a hands-on role requiring deep technical expertise, strong problem-solving skills, and the ability to learn and apply new technologies.  Key ResponsibilitiesData Pipeline Development: Design, build, and optimize robust batch and streaming pipelines using tools like Apache Spark, Flink, and Airflow. Data Crawling & Ingestion: Build scalable back-end services to crawl, ingest, and normalize data from web sources, APIs, databases, and flat files. Data Quality & Governance: Implement frameworks and tools (e.g., OpenMetadata, Collibra) to enforce data integrity, security, and compliance with Vietnamese data regulations. Data Modeling & Design: Define scalable data models and schemas using best practices (e.g., Kimball, Data Mesh, Data Fabric). Collaboration: Work with data scientists, analysts, engineers, and product teams to ensure the availability, usability, and performance of data pipelines. Monitoring & Troubleshooting: Proactively monitor data systems and resolve issues swiftly to ensure reliability and performance. Documentation: Create clear, comprehensive documentation for pipelines, tools, and processes. Mentorship: Support and guide junior data engineers through reviews, pairing, and best practices. Technology Evaluation: Stay updated on the latest technologies and recommend tools that improve data engineering workflows and scalability.