Build and maintain audience platform initiatives to improve and expand audience targeting capabilities.
Partner with technical and non-technical colleagues to understand audience data and targeting requirements.
Work with engineering teams to collect required data from internal and external systems.
Support Agile methodologies such as Scrum by actively participating in regular ceremonies such as stand-up, retrospectives and sprint planning.
Design table structures and define ETL pipelines to build performant and scalable solutions
Develop Data Quality checks
Participate in on-call support
Develop and maintain ETL routines using ETL and orchestration tools such as Airflow
Perform ad hoc analysis and SQL and ETL tuning as necessary.
Participate in code reviews and problem-solving.
Requirements
5+ years of big data engineering experience modeling and developing large data pipelines
Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark)
Strong Python and SQL skills processing big datasets
Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, Big Query, Databricks)
Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices
API and backend development experience
Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
Benefits
Health insurance
401(k) matching
Flexible work hours
Paid time off
Bonuses and/or long-term incentive units dependent on position
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