We are looking for an experienced and highly motivated Senior Data Engineer with high professional skills to join our AI, Data & Research unit. Spearhead the development of Data Lakehouse processes and modeling our products; Define and popularize best practices in the data field.
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 products and customers along with product managers and data scientists.
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 products and customers along with product managers and data scientists.
Requirements:
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.
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.
This position is open to all candidates.
