Inclusion Cloud
Azure Data Engineer (Lost)
Inclusion Cloud, Detroit, Michigan, United States, 48228
About the job Azure Data Engineer
About the client The client is an American automotive components original equipment manufacturer and an aftermarket ride control and emissions products manufacturer. It is a
Fortune
500 company located in Detroit. Role And Responsibilities Design and build data processing components and systems utilizing cloud compute technologies including Azure Cloud. Design requirement-driven data models such as dimensional, relational, and data vault. Build ELT/ETL pipelines using workflow management applications such as SSIS, Azure Data Factory, and distributed computing such as Synapse and Databricks Spark. Acquire, analyze, combine, synthesize, and store data from a wide range of internal and external sources as it pertains to system development. Experience with SAP systems will be a plus. Build and test CI/CD deployment pipelines for data system components. Develop and support monitoring solutions for data systems and components. Partner with business and technical leaders to prioritize data needs to expand the analytics solution capabilities. Qualifications And Education Requirements 5+ years of experience in data engineering, data warehousing, or a related field. Understanding of data lake design and implementation will be a plus. Mastery of SQL, with data warehouse design and implementation experience in cross-functional areas like Sales & Distribution, Supply Chain, Finance, Marketing, etc. Experience with SAP VMWare is a big plus. Experience building and automating data system components that enable data acquisition, cleansing, and persistence engineering. Experience with Azure technologies such as Azure Blob Storage, Azure Data Lake Storage Gen2, Azure SQL Database, etc. Experience with visualization tools like Power BI will be preferred. Monitoring the performance of data analysis and system components. Versioning of data snapshots, data lineage, schemas, and overall database systems. Deployment through a CI/CD pipeline with Azure DevOps preferred. Automated analysis optimizations based on performance metrics. Strong PowerShell and cloud compute skills. Experience with analytics tools such as Databricks Spark and PySpark. Experience with modern infrastructure as code technologies like Terraform. Experience with modern CI/CD pipeline technologies involving git repositories, static code analysis, and test-driven development. Experience in the full data engineering life-cycle, from business understanding to building operational systems. Understanding and awareness of regulations around the use of PII data. Understanding and experience navigating all types of database models and DBMSs. Must have excellent data problem-solving skills, communication skills, and can execute alone but is an awesome team player. Big picture approach a plus - able to incorporate business understanding into design and approach to achieve current value and prepare for future benefit. Consulting experience a plus; role includes client-facing meetings and communication. Excellent teamwork, coordination, influencing, and communication skills. Ability to develop timely and effective solutions for challenging design problems. Establishes relationships with data owners, experts, and SMEs across a wide variety of the client's data domains, including continual expansion of analytics capabilities to grow data expertise. B.S. degree in Computer Science or related fields.
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About the client The client is an American automotive components original equipment manufacturer and an aftermarket ride control and emissions products manufacturer. It is a
Fortune
500 company located in Detroit. Role And Responsibilities Design and build data processing components and systems utilizing cloud compute technologies including Azure Cloud. Design requirement-driven data models such as dimensional, relational, and data vault. Build ELT/ETL pipelines using workflow management applications such as SSIS, Azure Data Factory, and distributed computing such as Synapse and Databricks Spark. Acquire, analyze, combine, synthesize, and store data from a wide range of internal and external sources as it pertains to system development. Experience with SAP systems will be a plus. Build and test CI/CD deployment pipelines for data system components. Develop and support monitoring solutions for data systems and components. Partner with business and technical leaders to prioritize data needs to expand the analytics solution capabilities. Qualifications And Education Requirements 5+ years of experience in data engineering, data warehousing, or a related field. Understanding of data lake design and implementation will be a plus. Mastery of SQL, with data warehouse design and implementation experience in cross-functional areas like Sales & Distribution, Supply Chain, Finance, Marketing, etc. Experience with SAP VMWare is a big plus. Experience building and automating data system components that enable data acquisition, cleansing, and persistence engineering. Experience with Azure technologies such as Azure Blob Storage, Azure Data Lake Storage Gen2, Azure SQL Database, etc. Experience with visualization tools like Power BI will be preferred. Monitoring the performance of data analysis and system components. Versioning of data snapshots, data lineage, schemas, and overall database systems. Deployment through a CI/CD pipeline with Azure DevOps preferred. Automated analysis optimizations based on performance metrics. Strong PowerShell and cloud compute skills. Experience with analytics tools such as Databricks Spark and PySpark. Experience with modern infrastructure as code technologies like Terraform. Experience with modern CI/CD pipeline technologies involving git repositories, static code analysis, and test-driven development. Experience in the full data engineering life-cycle, from business understanding to building operational systems. Understanding and awareness of regulations around the use of PII data. Understanding and experience navigating all types of database models and DBMSs. Must have excellent data problem-solving skills, communication skills, and can execute alone but is an awesome team player. Big picture approach a plus - able to incorporate business understanding into design and approach to achieve current value and prepare for future benefit. Consulting experience a plus; role includes client-facing meetings and communication. Excellent teamwork, coordination, influencing, and communication skills. Ability to develop timely and effective solutions for challenging design problems. Establishes relationships with data owners, experts, and SMEs across a wide variety of the client's data domains, including continual expansion of analytics capabilities to grow data expertise. B.S. degree in Computer Science or related fields.
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