Data Engineer – ETL

Design, implement, and optimize data systems to support our data
mesh infrastructure.
– Utilize AWS Glue for data extraction, transformation, and loading
(ETL) processes.
– Refactor and improve existing data systems for enhanced
efficiency and performance.
– Collaborate closely with product development and production
support teams to meet their data engineering requirements.
– Participate actively in peer code reviews to maintain code quality
and consistency.
– Diagnose and resolve production issues, offering corrective
measures and workarounds when necessary.
– Continuously assess key performance indicators (KPIs) and
identify opportunities for improvements and optimizations within
our data mesh.

– Experience in building data systems with real-time data streams
(e.g., Kafka, Kinesis).
– Bachelor of Science degree in a technical major (Computer
Science, Engineering, Mathematics) or equivalent industry
experience.
– Familiarity with other ETL tools (Pentaho, Informatica, SSIS,
etc.).
– Knowledge or experience with microservices and messaging
systems.
– Experience with supply chain management is a plus.

Strong understanding of AWS services and AWS Glue, Athena
and Lambda Functions

– Minimum of 5 years of relevant experience in data engineering.
– Strong understanding of complex data architecture, especially for
data lake environments.
– Proficiency in ETL concepts within modern data applications.
– Excellent SQL skills, with a focus on PostgreSQL and query
optimization.
– Proficiency in Python programming.
– Familiarity with MongoDB is a plus.
– Familiarity with agile development practices.
– Demonstrated ability in analysis and design of data systems.