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Data Engineer (40000064)

Category:  Data and Analytics Division
Job Type: 
Facility:  Data & Analytics

Job Purpose

- The job holder is responsible for 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 helping build a reliable, sustainable and scalable data processing platform, working with other tribe members to support data pipelines, convert models to machine learning codes and recommend Big Data reporting and visualization applications.

Key Accountabilities (1)

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
Assist in building best practices and strategies for data infrastructure to fulfill data analytic and utilization needs of the business with emerging latest technologies and capabilities.
- Collaborate with relevant teams on opportunities to manage data and provide solutions for complex data feeds within the bank.
- Maintain data integration processes into the data platform by building data pipelines and align with business representatives and business information needs.
- Review 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
- Obtain and integrate data and information from various sources into the firm’s platforms, solutions and statistical models.
- Collaborate with Data Scientists to understand data requirements and create re-usable data assets to enable data scientists to build and deploy machine learning models faster.
- Write scripts and ingest raw data to build and maintain optimized data pipelines and ETL solutions as business support tools in providing analysis.
- Ensure data assets are organized and stored in an efficient way so that information is easy to access and retrieve.

Key Accountabilities (3)

Key Relationships - Direct 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

Success Profile - Qualification and Experiences

- Bachelor’s or Master’s degree in Statistics, Mathematics, Quantitative Analysis, Computer Science, Software Engineering or Information Technology
Work Experience
- 5+ 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
- Experience in designing and building dimensional data models, ETL processes, applied data warehouse concepts and methodologies, optimized data pipelines and assisted the architect as needed
- Experience 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 support digital transformation projects, having a clear understanding of Agile principles, practices and Scrum methodologies
- Has some know-how and partial scripting and coding experience to set up, configure và maintain a machine learning model development environment
- Some experience architecting, coding and delivering high performance micro services and/or recommenders delivering recommendations to a large user-base

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