126 to 150 of 1,038 PySpark Jobs

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and the broader Azure ecosystem. Requirements Proven experience as a Data Engineer working with Microsoft Fabric or related Azure data services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft More ❯

and performance Work within Azure Databricks and follow code-based deployment practices Must-Have Skills: 3 years of experience with Databricks (Lakehouse, Delta Lake, PySpark, Spark SQL) Strong SQL skills (5 years) Experience with Azure, focusing on Databricks Excellent client-facing communication skills Experience deploying Databricks pipelines and jobs More ❯

data. Proficient in coding in one or more languages Python, Pyspark. Demonstrable experience with Python and associated data manipulation libraries (NUMPY, PANDAS) Experience in PySpark, particularly Analysis, Building and Tuning Pipelines, Feature Engineering Working experience in NoSQL databases or SQL (e.g., joins, aggregations, tuning) Experience with ETL and processing More ❯

initiatives Key Requirements of the Database Engineer: Proven experience with Databricks, Azure Data Lake, and Delta Live Tables Strong programming in Python and Spark (PySpark or Scala) Solid knowledge of data modelling, warehousing, and integration concepts Comfortable working in Agile teams, with CI/CD and Azure DevOps experience More ❯

initiatives Key Requirements of the Database Engineer: Proven experience with Databricks, Azure Data Lake, and Delta Live Tables Strong programming in Python and Spark (PySpark or Scala) Solid knowledge of data modelling, warehousing, and integration concepts Comfortable working in Agile teams, with CI/CD and Azure DevOps experience More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

System Integration, Application Development or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. More ❯

structure and process improvement. What we value These skills will help you succeed in this role Strong skill-set, experience in Python, Scala/PySpark, PL/SQL, PERL/scripting . Skilled Data Engineer for Cloud Data Lake activities. The candidate should have industry experience (preferably in Financial More ❯

ETL/ELT processes. Advanced knowledge of Azure Data Factory V2, Azure Databricks, Azure Data Lake Gen2, and Azure Event Hubs. Proficiency in SQL, PySpark, and Python for data transformation and scripting. Hands-on experience with DevOps practices and managing CI/CD pipelines. Expertise in big data technologies More ❯