Quantitative Researcher

Senior Software Engineer (Data Management, Data Lake)

Ho Chi Minh - Viet Nam

Product

• Data Engineering
• Cloud
• Java
• Typescript
• Angular

We are looking for a seasoned Senior Data and Full-Stack Engineer to join our team. In this role, you will not only design and build high-performance, resilient data architectures but also craft scalable solutions that integrate seamlessly with microservice-based application ecosystems. Your expertise will span across data engineering and full-stack development, enabling you to deliver end-to-end solutions that power our platform. You will own critical design deliverables-both high and low level-including ERDs, logical and physical models, and architectural reviews. Beyond architecture, you will actively contribute to building robust services and APIs that leverage data for automation, customer experience optimization, and innovative product development. As Company continues to grow and data volumes surge, your ability to harness this data and translate it into actionable insights and advanced solutions will be pivotal to our success.#Your key responsibilities as a Senior Data & Full-stack Developer will include: Drive and design future-proof data architectures, strategically aligning data systems with business objectives to ensure efficient and scalable data management. Architecting conceptual, logical, and physical architecture and data models for operational enterprise data and analytics solutions using recognised data modelling approaches Collaboration with project teams to ensure architectural principles are met, and build and act as a change agent Build container-based big data architectures on top of Kubernetes Design and implement large and complex data solutions (Data Warehouse, Data Lake, Data Analytics) using various architectural patterns such as microservices Develop and understand the enterprise data landscape and map data stores and flows between the operational systems for our microservice approach Implementing the feature with high-performance, scalable, and testable components for our architecture and execute its development. Developing and deploying modern architectural patterns/techniques (microservices, DDD, TDD), including developing using modern frameworks, e.g. Spring Boot, Spring Cloud Developing and deploying modern frontend microservices, enrich DM Storybook using the latest Angular version. Develop RESTful APIs and microservices-based solutions leveraging containers (AKS, Kubernetes, Docker) technologies#General Create robust data architecture to manage data efficiently and effectively Define the data strategy and the key principles associated with it Develop and understand the enterprise data landscape and map data stores and -flows between the operational systems for our micro-service approach The role is varied and there are opportunities to become involved in activities across all parts of the business

Negotiation

Senior Data Engineer, Log Analytics

Ho Chi Minh - Viet Nam

Product

• Data Engineering

Take charge of creating cutting-edge technologies and strategies, focusing on visualizing and analyzing log data effectively. Precisely analyze Syslog and telemetry data to predict and categorize errors and job failures. Work with team members to set new technology directions and deploy advanced log analytics solutions. Collaborate with teams from different areas to identify effective data analysis strategies and methods.

Negotiation

Senior/ Lead Data Engineer (Data Platform / MLOps)

Ho Chi Minh, Ha Noi - Viet Nam

Outsource

You will be responsible for managing, designing, and enhancing data systems and workflows that drive key business decisions. The role is focused 75% on data engineering, involving the construction and optimization of data pipelines and architectures, and 25% on supporting data science initiatives through collaboration with data science teams for machine learning workflows and advanced analytics. You will leverage technologies like Python, Airflow, Kubernetes, and AWS to deliver high-quality data solutions. Architect, develop, and maintain scalable data infrastructure, including data lakes, pipelines, and metadata repositories, ensuring the timely and accurate delivery of data to stakeholders. Work closely with data scientists to build and support data models, integrate data sources, and support machine learning workflows and experimentation environments. Develop and optimize large-scale, batch, and real-time data processing systems to enhance operational efficiency and meet business objectives. Leverage Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoring. Utilize AWS services such as S3, Glue, EC2, and Lambda to manage data storage and compute resources, ensuring high performance, scalability, and cost-efficiency. Implement robust testing and validation procedures to ensure the reliability, accuracy, and security of data processing workflows. Stay informed of industry best practices and emerging technologies in both data engineering and data science to propose optimizations and innovative solutions.

Negotiation