
Data Engineer
2 weeks ago
**Job Summary**:
**Salary**
S$7,500 - S$11,500 / Monthly
**Job Type**
**Seniority**
Senior
**Years of Experience**
At least 6 years
**Tech Stacks**
ETL AWS Analytics pySpark Apache Azure Spark NoSQL SQL Python
**Position Overview**:
As a PySpark Data Engineer, you will be responsible for designing, implementing, and maintaining data processing pipelines using PySpark. You will work closely with our data scientists and analysts to understand requirements, transform raw data into usable formats, and optimize data workflows for performance and scalability.
**Responsibilities**:
- Collaborate with cross functional teams to understand data requirements and translate them into technical solutions.
- Implement efficient ETL processes to ingest, cleanse, transform, and store structured and unstructured data.
- Optimize PySpark jobs for performance, scalability, and reliability.
- Troubleshoot and debug data processing issues in production environments.
- Develop and maintain documentation for data pipelines, workflows, and data models.
- Stay current with emerging technologies and best practices in big data processing and analytics.
**Requirements**:
- Degree in computer science, Engineering, or a related field.
- 6-9 years of experience in data engineering with a focus on PySpark.
- Proficiency in Python programming language.
- Strong understanding of distributed computing principles and big data processing frameworks.
- Handson experience with Apache Spark, PySpark, and related technologies.
- Solid knowledge of SQL and experience working with relational and NoSQL databases.
- Experience with cloud platforms such as AWS, Azure, or GCP is a plus.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
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