RICEFW Technologies
Senior Data Engineer
RICEFW Technologies, Cincinnati, Ohio, United States, 45208
Please Note: As of July 22, 2021, our team will require that all candidate submissions include a LinkedIn profile. Please do not submit any candidates that do not have a LinkedIn.
NA has a client in Cincinnati, OH that is seeking 4 Senior Data Engineers to join their team on a 9-month contract to hire basis. We are seeking highly skilled Senior Data Engineers to join our team in building a cutting-edge data platform for the warehouse and manufacturing domains within the supply chain space.
Responsibilities:Design and implement robust data pipelines for high-throughput data ingestion, transformation, and storage.Optimize data processing workflows for performance and scalability in Azure cloud environments.Collaborate with data scientists and business analysts to understand requirements and deliver data engineering solutions that meet business objectives.Monitor and troubleshoot data pipeline failures, ensuring minimal downtime and maximum reliability.Draft architectural diagrams, interface specifications and other design documentsParticipate in the development and communication of data strategy and roadmaps across the technology organization to support project portfolio and business strategy.Innovate, develop, and drive the development and communication of data strategy and roadmaps across the technology organization to support project portfolio.Drive the development and communication of enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses.Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms.Define high-level migration plans to address the gaps between the current and future state, typically in sync with the budgeting or other capital planning processes.Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement.
Required Skills : - Possess strong technical proficiency in a variety of tools and technologies relevant to data engineering in Azure cloud environments. - Demonstrated expertise in Azure Databricks for building and optimizing data pipelines, as well as experience with Azure Synapse Analytics for data warehousing and analytics. - Proficiency in SQL is essential for querying and manipulating data within these platforms, along with programming skills in Python and PySpark for data processing and transformation tasks. - Experience working with distributed computing frameworks and familiarity with cloud-based storage solutions such as Azure Blob Storage and Azure Data Lake Storage. - Knowledge of data modeling, ETL processes, and data security best practices is also crucial for designing and implementing scalable and reliable data solutions. - Ability to troubleshoot and optimize data processing workflows, along with strong problem-solving skills, is essential for ensuring the performance and efficiency of data pipelines in high-throughput environments.Rank :A3Requested Date :2024-03-15
NA has a client in Cincinnati, OH that is seeking 4 Senior Data Engineers to join their team on a 9-month contract to hire basis. We are seeking highly skilled Senior Data Engineers to join our team in building a cutting-edge data platform for the warehouse and manufacturing domains within the supply chain space.
Responsibilities:Design and implement robust data pipelines for high-throughput data ingestion, transformation, and storage.Optimize data processing workflows for performance and scalability in Azure cloud environments.Collaborate with data scientists and business analysts to understand requirements and deliver data engineering solutions that meet business objectives.Monitor and troubleshoot data pipeline failures, ensuring minimal downtime and maximum reliability.Draft architectural diagrams, interface specifications and other design documentsParticipate in the development and communication of data strategy and roadmaps across the technology organization to support project portfolio and business strategy.Innovate, develop, and drive the development and communication of data strategy and roadmaps across the technology organization to support project portfolio.Drive the development and communication of enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses.Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms.Define high-level migration plans to address the gaps between the current and future state, typically in sync with the budgeting or other capital planning processes.Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement.
Required Skills : - Possess strong technical proficiency in a variety of tools and technologies relevant to data engineering in Azure cloud environments. - Demonstrated expertise in Azure Databricks for building and optimizing data pipelines, as well as experience with Azure Synapse Analytics for data warehousing and analytics. - Proficiency in SQL is essential for querying and manipulating data within these platforms, along with programming skills in Python and PySpark for data processing and transformation tasks. - Experience working with distributed computing frameworks and familiarity with cloud-based storage solutions such as Azure Blob Storage and Azure Data Lake Storage. - Knowledge of data modeling, ETL processes, and data security best practices is also crucial for designing and implementing scalable and reliable data solutions. - Ability to troubleshoot and optimize data processing workflows, along with strong problem-solving skills, is essential for ensuring the performance and efficiency of data pipelines in high-throughput environments.Rank :A3Requested Date :2024-03-15