Data and AI Tech Principal Specialist SG

Key Responsibilities:

• Assist Head of Data and AI in Data and AI -related projects and solutioning activities and ensure successful delivery and support of the project.
• Involve in the discussion with stakeholders on business application enhancements, to understand business requirements, participate in developing an effective and efficient solution.
• Involve in the technology related solution and delivery of projects for Bank applications
• Provides support to System Integration Testing (SIT) and User Acceptance Testing (UAT), prior to production implementation
• Schedule and support production maintenance activities, such as software deployments, security patches and operating system patches
• Attend to production problems on timely manner and escalate to management for their attention when necessary
• Work closely with external vendors and internal IT partners effectively in carrying out required assignments
• Compliance with external/internal regulatory requirements, internal control standards and group compliancy policy.
• Contribute to proper application documentation to build the knowledge assets for the Bank
• Participate actively in Department and Bank’s initiative and activities
• Design and maintain efficient data pipeline architectures to ensure seamless data flow and processing.
• Compile and manage extensive, intricate data sets that fulfill both functional and non-functional business requirements.
• Identify, design, and implement internal process enhancements by automating manual tasks, optimizing data delivery, and re-engineering infrastructure for improved scalability.
• Develop and maintain the infrastructure necessary for optimal data extraction, transformation, and loading (ETL) from diverse data sources using SQL and AWS big data technologies.
• Create advanced analytics tools that leverage the data pipeline to deliver actionable insights into customer acquisition, operational efficiency, and other critical business performance metrics.
• Collaborate with stakeholders including Executive, Product, Data, and Design teams to address data-related technical issues and support their data infrastructure needs.
• Ensure data security and compliance by maintaining data separation and security across multiple data centers.
• Develop data tools for the analytics and data science teams to aid in building and optimizing our product, positioning it as an innovative industry leader.
• Work closely with data and analytics experts to enhance the functionality and performance of our data systems.

Job Requirements:

University Bachelor's Degree preferably majoring in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field.

General Competencies & Skills

• Strong analytical and problem solving experience
• Detail-orientated with strong stakeholder and customer focus
• Strong verbal and written communication skills
• Excellent interpersonal skills
• Able to work as a team with active participation in team discussion, and also able to work independently to handle multiple tasks assigned
• Proactive and able to work under pressure and positive attitude
• Experience with documented evident on solutioning banking areas, preferably in transaction banking and development in modern technology frameworks and methodology
• Self-proficient MS Excel, PowerPoint and MS project

Technical/Professional Competencies & Skills

• 5-8 years' experience in Data Engineering
• Knowledge in application management and project SDLC, ITIL processes in a banking environment
• Experience in support and troubleshooting for Production and UAT/SIT (coordination and hands-on)
• Good sense in new technologies landscape
• Good communication skill and ability to present technical proposals to internal IT stakeholders
• Proficient in SQL with extensive experience in relational databases, query authoring, and familiarity with various database systems.
• Proven experience in building and optimizing big data pipelines, architectures, and data sets.
• Skilled in performing root cause analysis on internal and external data and processes to address specific business questions and identify improvement opportunities.
• Strong analytical skills for working with unstructured datasets.
• Experience in developing processes for data transformation, data structures, metadata, dependency, and workload management.
• Demonstrated success in manipulating, processing, and extracting value from large, disconnected datasets.
• Knowledgeable in message queuing, stream processing, and highly scalable big data stores.
• Excellent project management and organizational skills.
• Experience collaborating with cross-functional teams in a dynamic environment.
• Practical Knowledge of Linux or Unix shell scripting.
• Minimum of 5 years of experience in a Data Engineer role, with a graduate degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field. Additionally, experience with the following tools and technologies is required:
  • Big data tools: Hadoop, Spark, Kafka, etc.
  • Relational SQL and NoSQL databases: Postgres, Cassandra, etc.
  • Data pipeline and workflow management tools: AWS data pipeline, etc.
  • AWS cloud services: EC2, EMR, RDS, Redshift, Iceberg
  • Object-oriented and functional programming languages: Python, Java, C++, Scala, etc.