AI DATA ENGINEER
Posted
Summary
Builds and maintains the data infrastructure behind AI applications: designing ETL pipelines, optimizing storage and retrieval, ensuring data quality, and supplying datasets to data scientists. Core tech includes Python/Java/Scala, cloud data warehouses (Redshift/BigQuery/Snowflake), Hadoop/Spark/Kafka, and SQL/NoSQL databases.
Description
We are seeking an experienced AI Data Engineer to join our team in Southeast Asia. The ideal candidate will have a strong background in data engineering with a focus on building and maintaining data infrastructure for AI applications.
Responsibilities
Design and implement data pipelines for AI applications. Collaborate with data scientists to understand data requirements and provide necessary datasets. Optimize data storage and retrieval processes for efficiency and performance. Ensure data quality and integrity throughout the data lifecycle. Monitor and troubleshoot data systems and workflows.
Skills and Qualifications
4-5 years of experience in data engineering or a related field. Proficient in programming languages such as Python, Java, or Scala. Experience with data warehousing solutions such as AWS Redshift, Google BigQuery, or Snowflake. Familiarity with big data technologies like Hadoop, Spark, and Kafka. Strong understanding of database systems (SQL and NoSQL). Knowledge of machine learning concepts and data preprocessing techniques. Experience with ETL tools and data integration techniques.
We are seeking an experienced AI Data Engineer to join our team in Southeast Asia. The ideal candidate will have a strong background in data engineering with a focus on building and maintaining data infrastructure for AI applications.
Responsibilities
Design and implement data pipelines for AI applications. Collaborate with data scientists to understand data requirements and provide necessary datasets. Optimize data storage and retrieval processes for efficiency and performance. Ensure data quality and integrity throughout the data lifecycle. Monitor and troubleshoot data systems and workflows.
Skills and Qualifications
4-5 years of experience in data engineering or a related field. Proficient in programming languages such as Python, Java, or Scala. Experience with data warehousing solutions such as AWS Redshift, Google BigQuery, or Snowflake. Familiarity with big data technologies like Hadoop, Spark, and Kafka. Strong understanding of database systems (SQL and NoSQL). Knowledge of machine learning concepts and data preprocessing techniques. Experience with ETL tools and data integration techniques.