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- Design, develop, and maintain scalable data pipelines and ETL processes using Hadoop and Spark.
- Write efficient and optimized data processing jobs in Scala to transform and load data.
- Utilize SQL for querying and manipulating data across various databases.
- Collaborate with data scientists and analysts to gather requirements and deliver data solutions that meet business needs.
- Monitor and troubleshoot data processing workflows to ensure high performance and reliability.
- Implement best practices for data quality, governance, and security.
- Document data engineering processes, workflows, and architecture for team knowledge sharing.
- Stay updated on industry trends and emerging technologies to continuously improve our data strategies.
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- 3+ years of experience as a Data Engineer or in a similar role.
- Strong proficiency in Hadoop ecosystem components (e.g., HDFS, Hive, Pig).
- Hands-on experience with Apache Spark for big data processing.
- Proficient in Scala programming for data transformation tasks.
- Advanced SQL skills for querying and managing large datasets.
- Experience with data modeling, data warehousing, and ETL processes.
- Familiarity with cloud platforms (AWS, GCP, or Azure) is a plus.
- Strong analytical and problem-solving skills.
Unison Consulting Singapore, Singapore, SGP Office
Singapore, Singapore
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.
