Data Engineer in Lisbon, Portugal with a hybrid work arrangement at Celfocus is responsible for building and maintaining data platforms, focusing on data storage, processing, orchestration, and analysis across the organization. The role involves designing, developing, and maintaining scalable, high-performance data pipelines and data integration solutions, agnostic to data sources and technologies to enable data scientists, analysts, and other stakeholders to access data effectively. Key responsibilities include designing, building, and maintaining scalable data platforms; collecting, processing, and analyzing large and complex data sets from diverse sources; developing data processing workflows using Spark and Apache Beam; collaborating with cross-functional teams to ensure data accuracy and integrity; ensuring data security and privacy through proper access controls and encryption; extracting data from various sources such as databases, file systems, and APIs; monitoring system performance and optimizing for high availability and scalability. What we are looking for: Technical Skills Profile: Databricks & PySpark Developer. Databricks Ecosystem: proficiency in building and managing Databricks Workspaces and Notebooks; experience with Unity Catalog for data governance; knowledge of Databricks Workflows (Jobs, Orchestration). Distributed Computing (PySpark): strong hands-on experience with PySpark DataFrames, Datasets, and RDDs; deep understanding of Spark architecture; ability to tune and optimise Spark applications. Languages & Data Warehousing: Python with data analysis

Data Engineer in Lisbon, Portugal with a hybrid work arrangement at Celfocus is responsible for building and maintaining data platforms, focusing on data storage, processing, orchestration, and analysis across the organization. The role involves designing, developing, and maintaining scalable, high-performance data pipelines and data integration solutions, agnostic to data sources and technologies to enable data scientists, analysts, and other stakeholders to access data effectively. Key responsibilities include designing, building, and maintaining scalable data platforms; collecting, processing, and analyzing large and complex data sets from diverse sources; developing data processing workflows using Spark and Apache Beam; collaborating with cross-functional teams to ensure data accuracy and integrity; ensuring data security and privacy through proper access controls and encryption; extracting data from various sources such as databases, file systems, and APIs; monitoring system performance and optimizing for high availability and scalability. What we are looking for: Technical Skills Profile: Databricks & PySpark Developer. Databricks Ecosystem: proficiency in building and managing Databricks Workspaces and Notebooks; experience with Unity Catalog for data governance; knowledge of Databricks Workflows (Jobs, Orchestration). Distributed Computing (PySpark): strong hands-on experience with PySpark DataFrames, Datasets, and RDDs; deep understanding of Spark architecture; ability to tune and optimise Spark applications. Languages & Data Warehousing: Python with data analysis