Senior Data Engineer - Toa Payoh

• Develop, maintain scalable data pipelines and build out new integrations to support continuing increases in data volume and complexity
• Develop and maintain scalable, optimized data pipelines leveraging Python and AWS services to support increasing data volume and complexity, while ensuring seamless integration with AI platforms like Bedrock and Google
• Further enhance data accessibility and drive data-driven decision making by collaborating with analytics and business teams to refine data models for business intelligence tools
• Develop data models, schemas, and standards that ensure data integrity, quality, and accessibility
• Develop, maintain, and optimize scalable data pipelines using Python and AWS services (e.g., S3, Lambda, ECS, EKS, RDS, SNS/SQS, Vector DB)
• Build solutions with AI Services like Bedrock, Google etc.
• Rapidly developing next-generation scalable, flexible, and high-performance data pipelines
• Collaborate with analytics and business teams to create and improve data models for business intelligence
• End-to-end ownership of data quality in our core datasets and data pipelines
• Participate in code reviews and contribute to DevOps / DataOps / MLOps

Job Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field
• 5-6 years of experience in data engineering or a similar role
• Strong programming skills in Python, SQL, AWS and related tech stack
• Experience with building scalable data pipelines with technologies such as Glue, Airflow, Kafka, Spark etc.
• Experience using Snowflake, DBT, Bedrock is a plus
• Good understanding of basic machine learning concepts (Sagemaker)