Job Description

Income is looking for Lead Data Infrastructure Engineer to join our Data Engineering team in Singapore. Our team owns and runs the Enterprise Datalake used by thousands of users and hosted across AWS, GCP and On-Premises servers.

As a Data Infrastructure Engineer, you will design, build, maintain and improve our data infrastructure on Cloud, which enables us to make Income data driven organisation. In this role, you would also get the opportunity to work with world-class big data and cloud services, such as: AWS/GCP, Glue, Spark, DBT, Airflow, Tableau and PowerBI.

Responsibilities

• Work with data engineering and machine learning teams to improve our data infrastructure for increased reliability, maintainability, and scalability.
• Architect and design solutions to improve our data delivery capabilities, data quality monitoring, and data pipeline lifecycle.
• Architect and administer our cloud applications such as AWS Glue, Sagemaker, LakeFormation, Iceberg Lakehouse, etc.
• Managing Regression Testing Suite, Continuous Integration and Continuous deployment Pipelines.

• Bachelors Degree in Computer Science, Information Technology or other relevant fields
• 5+ years of designing and building Large Scale Infrastructure and ETL deployment and management pipelines using Terraform, Jenkins, AWS CodePipeline and AWS CodeBuild.
• At least 1-2 years of team leading experience and lead a team at least 2-3 team members in a project.
• Broad experience in SQL and Python.
• Hands-on experience of writing, building and deploying Containerised applications using ECS or EKS or GKE.
• Experience in cloud application architecture & administration in AWS or GCP.
• Hands-on experience designing, building, and operationalizing large-scale enterprise data solutions and applications. (AWS, Glue, Spark, Lambda, Sagemaker, DBT, Airflow, Tableau, PowerBI and Cloud storage preferred).
• Background in in custom ETL design, implementation, and maintenance.
• Hands-on experience with strong exposure to AWS CLI and BOTO3 Python libraries.