Scalable Data Solutions Engineer

1 week ago

Singapore beBeeDataEngineering Full time $90,000 - $120,000
Data Engineering Expert for Scalable Data Processing

We are seeking a highly skilled Data Engineering Lead to design and implement scalable data processing pipelines using Apache Spark and PySpark. As a key member of our team, you will be responsible for building, maintaining, and optimizing ETL processes for seamless data extraction, transformation, and loading across various data sources and destinations.

The ideal candidate should possess expertise in large-scale data processing and transformation using Apache Spark and PySpark. Hands-on experience with AWS Glue for building and managing ETL workflows in the cloud is required. Strong programming skills in Python, with experience in data manipulation, automation, and integration with Spark and Glue, are essential.

In-depth knowledge of ETL principles and data pipeline design, including optimization techniques, is necessary. Proficiency in working with AWS services such as S3, Glue, Lambda, and Redshift is expected, along with strong skills in writing optimized SQL queries focusing on performance tuning.

The successful candidate will have the ability to translate complex business requirements into practical technical solutions, familiarity with Apache Airflow for orchestrating data workflows, and knowledge of data warehousing concepts and cloud-native analytics tools. We offer a dynamic work environment where collaboration with data analysts, data scientists, and other engineering teams will be essential to create reliable data solutions that support business analytics and decision-making.

Maintaining clear documentation of processes, workflows, and code while adhering to best practices in data engineering, cloud architecture, and ETL design is also a key aspect of the role. If you meet these qualifications and are looking to join a forward-thinking organization, we encourage you to apply for this position.

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