About
We are looking for a seasoned Data Engineer to join our growing data team. Responsibilities
Own and lead the development of scalable, efficient, and robust data pipelines (ETL/ELT) from ingestion to delivery. Design and implement data processing workflows to support business analytics and machine learning. Drive the migration of our current Hadoop-based infrastructure to a Spark-based architecture on AWS. Collaborate with cross-functional teams including data analysts, data scientists, and software engineers to define data requirements and optimize data flow. Ensure data quality, observability, and compliance across systems. Requirements
4+ years of hands-on experience as a Data Engineer. Strong programming skills in Python and advanced proficiency in SQL. Hands-on experience with developing ETL/ELT pipelines using Spark and SQL. Experience working with cloud-hosted data warehouses such as Hive, Snowflake. Solid understanding and experience with the Hadoop ecosystem and distributed computing tools (e.g., EMR, Hive, Presto/Trino, Athena, AWS Glue). Proven expertise in data warehousing concepts, data modeling, and best practices. BA/BSc in Computer Science, Engineering, Information Systems, or equivalent. Excellent analytical skills and a strong attention to detail. Strong communication skills in English (written and verbal). Demonstrated ability to work both independently and in a collaborative team environment. Will Be A Plus
Familiarity with Kafka, Confluent, Fluentd, Spark, and Airflow. Experience with data visualization tools (e.g., Tableau). Previous experience in the media or TV industry. What We Offer
Flexible work arrangements. 20 working days per year is a non-operational allowance and settled to be used for personal recreation matters and are compensated in full. Collaborative and supportive team culture. Truly competitive salary. Help and support from our caring HR team.
Languages
- English
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