Data Architecture
- Deliver functionality required for business and data analysts, data scientists and other business roles to advance the overall analytic performance and strategy of the bank
- Build the best practices and strategies for data infrastructure to fulfill data analytic and utilization needs of the business with emerging latest technologies and capabilities.
- Proactively drive the effort of identifying opportunities to manage data and provide solutions for complex data feeds within the bank.
- Evaluate various data architectures in the bank and utilize them to develop data solutions to meet business requirements.
- Drive the delivery of data products and services into systems and business processes in compliance with internal regulatory requirements.
- Oversee the review of internal and external business and product requirements for data operations and activity and suggests changes and upgrades to systems and storage to accommodate ongoing needs.

Key Accountabilities (2)
Data Integration
- Strategically obtain and integrate data and information from various sources into the firm’s platforms, solutions and statistical models.
- Lead discussion with Data Scientists to understand the data requirements and create re-usable data assets to enable data scientists to build and deploy machine learning models faster.
- Design, build, and maintain optimized data pipelines and ETL solutions as business support tools in providing analysis and real time analytics platform for critical decision making.
- Ensure data assets are organized and stored in an efficient way so that information is high quality, reliable, flexible, and efficient.

Key Accountabilities (3)
Project Management
- Manage project conflicts, challenges and dynamic business requirements to keep operations running at high performance.
- Work with team leads to resolve people problems and project roadblocks, conduct post mortem and root cause analysis to help squads continuously improve their practices to ensure maximum productivity.
Talent Development
- Mentor and coach junior fellows into fully competent Data Engineers.
- Identify and encourage areas for growth and improvement within the team.

- The job holder is responsible for designing and developing programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from disparate sources and implement complex business logic as needed with the available data processing tools.
- The job holder will be responsible for integrating new data sources to increase throughput of existing systems, managing data pipelines that facilitate robust analysis, and sourcing và preparing data to ensure data completeness on metadata platforms.

Qualifications
- Bachelor's or Master’s degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology
Work Experience
- 7+ years of relevant experience with developing, debugging, scripting and employing big data technologies (e.g. Hadoop, Spark, Flink, Kafka, Arrow, Tableau), database technologies (e.g. SQL, NoSQL, Graph databases), and programming languages (e.g. Python, R, Scala, Java, Rust, Kotlin) with preference towards functional/trait oriented
- English proficiency requirements are pursuant to Techcombank's policy
- Deep experience in designing and building dimensional data models, ETL processes, applied data warehouse concepts and methodologies, optimized data pipelines and wore the architect hat in the past or worked with one extensively
- Deep experience with monitoring complex system and solving data and systems issues having a consistent and algorithmic approach to resolving them
- Deep understanding of Information Security principles to ensure compliant handling and management of all data
- Experience working in Agile teams to lead successful digital transformation projects, having mastered Agile principles, practices and Scrum methodologies
- Has the know-how and the scripting and coding prowess to set up, configure và maintain a machine learning model development environment
- Experience architecting, coding and delivering high performance micro services and/or recommenders delivering recommendations to (tens of) millions of users

Key Relationships - Direct Manager
Senior Manager / Manager, Data Engineering

Key Relationships - Direct Reports
Key Relationships - Internal Stakeholders
Teams within the Data Office and relevant departments in the Bank

Key Relationships - External Stakeholders
Partners providing professional services

Design and develop data processing systems (data pipelines, ETL/ELT)
Build and maintain workflow automation solutions (RPA, orchestration, workflow engines)
Deploy and manage applications on AWS Cloud
Apply AI/ML/LLM to use cases such as:
Automated document and record processing
Data analysis and decision support
Internal chatbots and AI agents
Integrate systems with internal platforms and third-party services (APIs, microservices)
Ensure system performance, scalability, and security
Collaborate with business teams to translate requirements into technical solutions

'We are looking for a Senior AI Engineer to design and build intelligent automation solutions for the Bank’s Operations Division and (DWH/Datalake) system operation. This role focuses on optimizing processes, reducing manual effort, and improving operational efficiency through data, cloud, build real AI-driven automation systems, not just prototypes. Become a key contributor in the organization’s digital transformation journey

Minimum 3–5 years of experience in software development (Backend/Data/Platform)
Proficiency in at least one programming language: Python / Java / Node.js
Strong experience with:
Data processing: SQL, NoSQL, Spark, Airflow, or equivalent tools
Designing and building data pipelines
Hands-on experience with AWS services:
(EC2, S3, Lambda, RDS, Glue, Step Functions, ECS/EKS, etc.)
Familiarity with:
AI/ML or LLM frameworks (e.g., OpenAI, Hugging Face, LangChain)
Automation use cases, AI agents, or workflow automation systems
Solid understanding of system design (microservices, event-driven architecture)
Strong problem-solving skills and ability to work independently

Experience in Banking / Financial Services
Experience with:
Kafka, Docker, Kubernetes
CI/CD and DevOps practices
Experience building automation platforms or AI-driven products

Continuous Delivery through DevSecOps Factory
- Build, map and optimize delivery of the Continuous Delivery Pipeline (CDP) by addressing key elements like: process time, lead time, delay time and percent of complete and accurate.
- Continuous Exploration (CE) – understand the market problem / customer need by analyzing and researching to identify the solution required to meet that need, from which suggest development of new features or modification from existing architectures, define and prioritize activities in the Program Backlog.
- Continuous Integration (CI) – take features from the Program Backlog and implement them to deliver a completed work which is committed to version control, built and integrated into a full system or solution, and tested end-to-end before being validated in a staging environment.
- Continuous Deployment (CD) - take the changes from the staging environment and deploy them to production.
- Release on Demand (RoD) - make value available to customers all at once, or in a staggered fashion based market and business needs.

Key Accountabilities (2)
DevSecOps Factory
- Build, automate, enhance and measure DevSecOps factory.
- Build, automate, enhance and integrate threat modeling.
- Build, automate, enhance and integrate application security.
- Build, automate, enahnce and integrate penetration testing.
- Build, automate, enhance and integrate continious security monitoring.

Key Accountabilities (3)
DevSecOps Targets
- Consistently develop software systems with higher quality and accuracy of project budgeting and estimation.
- Increase visibility and stakeholder input into features for the next release as it is being developed.
- Engage stakeholders early and consistently throughout the SDLC, leading to few defects and incorrect requirements.
- Build trust between software development and IT, enable organic process improvement and risk mitigation.
- Maximize business value by enabling technical staff to adapt to changing requirements or environmental factors.

- The job holder responsible for ensuring DevOps becomes a mindset, a culture, and a set of technical practices.
- The job holder will provide communication, integration, automation, and close cooperation among all the people needed to plan, develop, test, deploy, release, and maintain a Solution.
- The job holder will technically lead DevOps team to design and enhance the Continuous Delivery Pipeline (CDP) that represents the workflows, activities, and automation needed to shepherd a new piece of functionality from ideation to an on-demand release of value to the end user

Qualifications
- Bachelor's or Master’s degree in computer science, software engineering or information technology
Work Experience
- At least 7 years of relevant experience in software development and minimum 2 years of experience in DevSecOps setup.
- Knowledge of DevSecOps factory pipeline components and DevSecOps Metrics.
- Experience working with cloud environments is a must.
- Hands-on experience on code, commit, code review, document, test, integrate, qa, monitor with front end and back end languages and technologies.
- Experience working with DevSecOps tools is a must (RE protection, SSL pinning, payload encryption, Code quality, source code analysis, SAST/DAST tools).
Foreign language
- English/ according to TCB's regulations in each period

Key Relationships - Direct Manager
Manager/ Senior Manager/ Director, DevSecOps

Key Relationships - Direct Reports
Key Relationships - Internal Stakeholders
Key Relationships - External Stakeholders
Application/solution provider partners, IT departments of key customer businesses

Data Solutioning
- Build algorithms and work with machine learning and deep learning tools to deliver advance analytics solutions across the firm including recommendation engines, customized data models, customer journeys, graph modes, etc.
- Mine and analyze data from company’s databases to drive optimization and improvement of business strategies.
- Use predictive modelling to increase and optimize customer journey experiences, revenue generation and other business outcomes.
- Analyze data for trends and patterns and interpret the data with clear objective in mind.
- Execute and review data science projects in an agile manner and in compliance with internal regulatory requirements.

Key Accountabilities (2)
Data Insighting
- Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Interact with 1-2 squads to identify questions and issues for data analysis.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Key Accountabilities (3)
Key Relationships - Direct Manager
Manager, Data Science

Key Relationships - Direct Reports
Key Relationships - Internal Stakeholders
Teams within the Transformation Office and relevant departments in the Bank

Key Relationships - External Stakeholders
Partners providing professional services

- The job holder advises and provides business with insights from massive amounts of structured and unstructured potential data to help shape or meet specific business objectives.
- The job holder will build data science solutions using advance machine learning and deep learning methods, recommendation engines, statistical analysis, data mining and data visualization techniques, to create solutions that enable enhanced business performance.

Qualifications
- Bachelor's degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology
Work Experience
- 5+ years of relevant experience in areas of data analysis, machine learning, deep learning model development on large amount of data, implementing and deploying various statistical models
- English proficiency requirements are pursuant to Techcombank's policy
- Experience in querying databases and using programming languages (e.g. C, C++, R, Python, Scala, SQL, Java, Tableau, R)
- Experience communicating complex analysis and models across a diverse team
- Experience using of data optimization (linear / non-linear) to solve constrained business problems
- Understanding of Agile principles, practices and Scrum methodologies
- Experience working in Agile teams to support digital transformation projects

Key Relationships - Direct Manager
Manager, Data Science

Key Relationships - Direct Reports
Key Relationships - Internal Stakeholders
Teams within the Transformation Office and relevant departments in the Bank

Key Relationships - External Stakeholders
Partners providing professional services

Data Solutioning
- Build algorithms and work with machine learning and deep learning tools to deliver advance analytics solutions across the firm including recommendation engines, customized data models, customer journeys, graph modes, etc.
- Mine and analyze data from company’s databases to drive optimization and improvement of business strategies.
- Use predictive modelling to increase and optimize customer journey experiences, revenue generation and other business outcomes.
- Analyze data for trends and patterns and interpret the data with clear objective in mind.
- Execute and review data science projects in an agile manner and in compliance with internal regulatory requirements.

Key Accountabilities (2)
Data Insighting
- Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Interact with 1-2 squads to identify questions and issues for data analysis.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.

- The job holder advises and provides business with insights from massive amounts of structured and unstructured potential data to help shape or meet specific business objectives.
- The job holder will build data science solutions using advance machine learning and deep learning methods, recommendation engines, statistical analysis, data mining and data visualization techniques, to create solutions that enable enhanced business performance.

Qualifications
- Bachelor's degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology
Work Experience
- 5+ years of relevant experience in areas of data analysis, machine learning, deep learning model development on large amount of data, implementing and deploying various statistical models
- English proficiency requirements are pursuant to Techcombank's policy
- Experience in querying databases and using programming languages (e.g. C, C++, R, Python, Scala, SQL, Java, Tableau, R)
- Experience communicating complex analysis and models across a diverse team
- Experience using of data optimization (linear / non-linear) to solve constrained business problems
- Understanding of Agile principles, practices and Scrum methodologies
- Experience working in Agile teams to support digital transformation projects

Key Relationships - Direct Manager
Manager, Data Science

Key Relationships - Direct Reports
Key Relationships - Internal Stakeholders
Teams within the Transformation Office and relevant departments in the Bank

Key Relationships - External Stakeholders
Partners providing professional services

1. Low-Level Architecture Design & Development
- Contribute to low-level architecture design and develop software components that meet efficiency, scalability, and security standards.
- Work closely with architects and senior engineers to optimize system design and implementation.

2. Technical Mentorship & Process Improvement
- Guide Officer-level engineers, providing mentorship on best practices, coding standards, and development workflows.
- Identify areas for process improvements and drive adoption of engineering best practices within the team.

Key Accountabilities (2)
'3. Code Quality & Optimization
- Lead peer code reviews, enforce coding standards, and improve overall code maintainability.
- Optimize software for performance, scalability, and security, ensuring high reliability in production environments.

4. Testing & Debugging
- Conduct unit testing, integration testing, and contract testing to ensure software reliability.
- Collaborate with QE teams to diagnose, troubleshoot, and resolve complex defects in a timely manner.
- Promote test automation to improve software stability and release efficiency.

Key Accountabilities (3)
5. Technical Documentation
- Create and maintain clear, structured documentation, including:
- API specifications
- System design documents
- Coding and architectural guidelines
- Ensure documentation is regularly updated and aligned with system changes.

'The Expert, Software Engineering role within TechcomBank’s IT Division – Development Engineering function is responsible for providing deep technical expertise, leading complex software development projects, and driving innovation. Experts are expected to mentor both junior and senior engineers, contribute to system architecture, and implement best practices to ensure high-quality, scalable, and secure software solutions.

Qualifications:
- Bachelor's or Master's Degree in Computer Science, Software Engineering, Information Technology, or a related field.

Work Experience:
- At least 5 years of experience in the engineering field.
- At least 2 years in a Team lead position.
- Proficiency in programming languages related to application development.
    + Backend: Java
    + Web: Typescript
    + Mobile: Swift, Kotlin, Dart
- Experience in managing technical teams and mediating in the work environment.
- Experience in leading and managing system/software delivery.
- Experience in both architecture and software design implementation.
    + SOLID Principle
    + Design Patterns
    + Microservices architectures
    + Observability (monitoring, logging, tracing)
    + Compiling, Runtime deep understanding
- Experience in advanced aspect of engineering field:
    + High performanace, concurrency
    + Security best practices
    + Emerging technology

Foreign Language:
- English as per the organization's regulations

Key Relationships - Direct Manager
Head of Software Engineeing/ CTO/ Director, Software engineering

Key Relationships - Direct Reports
Staffs under team

Key Relationships - Internal Stakeholders
Division, units, branches/subsidiaries of TCB

Key Relationships - External Stakeholders
Application/solution provider partners, IT departments of key customer businesses