Data Engineer(Python + Airflow + Snowflake) at Rapsys Technologies
Singapore 787336, , Singapore -
Full Time


Start Date

Immediate

Expiry Date

04 Dec, 25

Salary

9000.0

Posted On

06 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Aws, Snowflake, Data Processing, Addition, Health Insurance, Data Modeling, Collaborative Environment, Computer Science, Data Engineering, Glue, Big Data, Sql, Hadoop, Communication Skills, Spark, Bitbucket, Python

Industry

Information Technology/IT

Description

REQUIREMENTS

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • Proficiency in Python, PySpark and SQL for data processing and manipulation.
  • Min 5 years of experience in data engineering, specifically working with Apache Airflow and AWS technologies.
  • Strong knowledge of AWS services, particularly S3, Glue, EMR, Redshift, and AWS Lambda.
  • Understanding of Snowflake Data Lake is preferred.
  • Experience with optimizing and scaling data pipelines for performance and efficiency.
  • Good understanding of data modeling, ETL processes, and data warehousing concepts.
  • Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
  • Effective communication skills and the ability to articulate technical concepts to
    non-technical stakeholders.

PREFERRED QUALIFICATIONS:

  • AWS certification(s) related to data engineering or big data.
  • Experience working with big data technologies like Snowflake, Spark, Hadoop, or

related frameworks.

  • Familiarity with other data orchestration tools in addition to Apache Airflow.
  • Knowledge of version control systems like Bitbucket, Git.

Job Type: Contract
Contract length: 12 months
Pay: $8,000.00 - $9,000.00 per month

Benefits:

  • Health insurance

Work Location: In perso

How To Apply:

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Responsibilities
  • Design, develop, and maintain complex data pipelines using Python for efficient data processing and orchestration.
  • Collaborate with cross-functional teams to understand data requirements and architect robust solutions within the AWS environment.
  • Implement data integration and transformation processes to ensure optimal performance and reliability of data pipelines.
  • Optimize and fine-tune existing data pipelines / Airflow to improve efficiency,scalability, and maintainability.
  • Troubleshoot and resolve issues related to data pipelines, ensuring smooth operation and minimal downtime.
  • Work closely with AWS services like S3, Glue, EMR, Redshift, and other related technologies to design and optimize data infrastructure.
  • Develop and maintain documentation for data pipelines, processes, and system architecture.
  • Stay updated with the latest industry trends and best practices related to data engineering and AWS services.
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