134 warehouse English-speaking jobs in Lisbon

Bash/Python/Go/Ruby), ETL, Spark, Amazon Web Services (AWS), good communication skills,, CI/CD, Data Warehouse

understanding of the software development cycle (development, deployment & support of large-scale data lake / warehouse

Deep familiarity with data architectures (data lakehouse, warehouse, streaming systems) Strong scripting

expertise in building and maintaining data pipelines, systems, and applications; • Proficient in data warehouse

Bash/Python/Go/Ruby), ETL, Spark, Amazon Web Services (AWS), good communication skills,, CI/CD, Data Warehouse

BI Engineer / Data Warehouse Developer / Azure Data Engineer We’re unlocking community knowledge in

Visualization: Sigma, Tableau, Looker, PowerBi ETL: DBT, AWS Glue , Cloud Data Warehouse: AWS Redshift

Architect Senior Solutions Architect & Consultant in Portugal (m/f/d) Senior Software Architect (m/f/d) - Warehouse

Event Operations Manager - Fully Remote in Portugal Operations Manager - Warehousing (French Speaker) Warehouse

. - Craft detailed budgets for plant and warehouse operations, as well as procurement activities. - Generate

. - Craft detailed budgets for plant and warehouse operations, as well as procurement activities. - Generate

data lakes); Knowledge of cloud-based data platforms and services (e.g., AWS Redshift, Azure SQL Data Warehouse

Director ELMAC Global Strategic Sourcing Strategic Sourcing - Senior Professional (P3) Warehouse Operations

experience in business and data analysis, experience in Power BI and data modeling Background in data warehouse

experience in business and data analysis, experience in Power BI and data modeling Background in data warehouse

Manage ETL processes to extract, transform, and load data into the warehouse.

Google Continue with Google Product Specialist - SAP MM Procurement & Supply Chain Analyst Sap Business Warehouse

is new and looking for Senior engineers who will help us build backend services, integrate with data warehouse

experience in semantic modelling of complex data landscapes and are familiar withconcepts of Data Lake, Data Warehouse

experience with cloud platforms (e.g., GCP, AWS), big data technologies (e.g., Spark, Hadoop), Data Warehouse