Manage the end to end data pipelines that pull data from operational system and from different end points, transform and load the data to the company data lake
Current environment is set up on hadoop, but the team will be responsible to complete migration to a new Spark based environment on AWS
Qualifications :
4+ years of hands-on experience as a Data Engineer
BA / BSc in a related field such as CS, engineering, information systems, or equivalent.
High proficiency in SQL & Python
Experience working with cloud-hosted data warehouses (Hive, Snowflake)
Hands-on experience with developing end-to-end ETL / ELT processes (Spark and SQL)
Experience with the Hadoop framework and parallel computing (EMR, HIVE, Presto / Trino / Athena, Glue)
Proven experience with data warehousing, modeling paradigms, and architectures, proficient in DWH methodologies and best practices
Will be a plus :
Familiar with Kafka, Confluent, Fluentd, Spark, and Airflow
Experience with data visualization tools such as Tableau
Experience with the media or TV industry - an advantage
Soft skills :
Strong analytical skills and attention to detail
Team player
Ability to handle several tasks simultaneously
Comfortable working independently and leading projects from end to end
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