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Senior Data Engineers at Thoughtworks develop, maintain, and test data applications, focusing on creating data solutions and pipelines.
Top Skills:
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Artificial Intelligence • Fintech • Payments • Financial Services • Generative AI
As a Senior Data Platform Engineer, you'll optimize data processing and storage, develop distributed systems, and guide junior engineers.
Top Skills:
BigQueryData LakeDbtFlinkHadoopJavaKafkaKotlinPythonScalaSnowflakeSparkSpring BootSQL
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The Senior Data Engineer will manage patent data operations, analyze data requirements, optimize data frameworks, and collaborate on architecture upgrades.
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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.
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).
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BUSINESS SEGMENTCorporatePLATFORMOperating DivisionKeppel Singapore Office
1 HarbourFront Avenue, Level 2, Keppel Bay Tower, Singapore, 098632
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
