The Senior Data Engineer will develop and maintain scalable data pipelines, enhance data accessibility, collaborate with teams for data modeling, and ensure data quality.
JOB DESCRIPTION
- 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
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).
#LI-JL2
BUSINESS SEGMENT
CorporatePLATFORMOperating Division
Top Skills
Airflow
AWS
Bedrock
Dbt
Glue
Kafka
Python
Sagemaker
Snowflake
Spark
SQL
Keppel Singapore Office
1 HarbourFront Avenue, Level 2, Keppel Bay Tower, Singapore, 098632
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