Your tasks

• Your responsibilities will include performance tuning and optimization of existing solutions, building and maintaining ETL pipelines, as well as testing and documenting current data flows
• You will also be involved in implementing tools and processes to support data-related projects and promoting the best development standards across the team
• Design, build, test and deploy Cloud and on-premise data models and transformations in Cloud Native or dedicated toolset
• Optimize data views for specific visualization use cases making use of schema design partitions, indexes, down-sampling, archiving, etc. to manage trade-offs such as performance and flexibility
• Review and refine, interpret and implement business and technical requirements
• Ensure you are part of the on-going productivity and priorities by refining User Stories, Epics and Backlogs in Jira
• Onboarding new data sources, design, build, test and deploy Cloud data ingest, pipelines, warehouse and data models/products

Your skills

• At least 4 years of commercial experience as a Data Engineer
• Strong Python and PySpark skills
• Strong hands-on experience with SQL and query optimization
• Experience with ETL/ELT pipelines development, testing,and management
• Strong experience with Hadoop
• Understanding of key concepts around Data Warehousing, Data Lakes and Data Lakehouses
• Experience with Cloud Data engineering toolset, preferably GCP

Nice to have

• Experience with Java/Scala

This possibility applies to work on a B2B basis.