Work closely with ML, Data engineers and architects from the AI, Data & Research unit as well as R&D software engineering teams.
identify opportunities and help specify data requirements to improve security for our company products and customers along with product managers and data scientists.
What you need to succeed:
5+ years of data modeling techniques and concepts – such as Facts, Dimension, Partitions, etc.
5+ years of experience in designing and implementing data ingestion, ETL processes and 3rd party tools, preferably with experience in Data Lakehouse and Data Warehouse architecture
5+ years of hands-on experience in SQL and Python / Pyspark (or Java / Scala)
Data landscape understanding from vendor-specific to open-source (e.g. Snowflake/Redshift, DataBricks, Iceberg, Hadoop, DBT)
A versatile, proactive, team player, can-do attitude, quick learner, and a great executor
How you will stand out from the crowd:
Data Warehouse technologies (especially Iceberg or Snowflake)
AWS ecosystem (Glue, Athena, Kinesis, Redshift, SageMaker, EMR) an advantage
Experience with Data Science (Scikit-learn / TensorFlow / PyTorch, etc.) an advantage
Background in cyber security an advantage
Managerial experience in the data engineering field an advantage.
