- Proven work history with Dedicated SQL Pools.
- Microsoft Azure Synapse Analytics experience is essential. (Dedicated SQL Pool, Azure Data Factory, Azure Storage)
- Design and implement end-to-end data solutions using Azure Synapse.
- Will likely have a degree in Computer Science, Statistics, Informatics, Information Technology or quantitative field.
- Excellentcommunication skills with the ability to work within a team, across the business, and build strong relationships.
- End-to-end Data Warehouse experience: ingestion, ETL, big data pipelines, data architecture, message queuing, stream processing, BI/Reporting, and Data Security.
- Abilityto build processes supporting data transformation, data structures, metadata, dependency, and workload management, as well as the ability to manipulate,process, and extract value from large, disconnected structured and unstructureddatasets.
- Advanced SQL/relational database knowledge (including SSIS), query authoring (SQL).
- Experience performing root cause analysis on data, answering specific business questions, and identifying opportunities for improvement.
- Understanding of machine learning and artificial intelligence ML libraries and frameworks (TensorFlow, Spark, etc).
- Experience with Data Governance (Quality, Lineage, Data dictionary, and Security).
- Proficiency in programming language such as Python or equivalentfor data engineering tasks.
- Familiarity with Git for version control and Azure DevOps for continuous integration and continuous deployment (CI/CD) processes.
External Skills And Expertise
- Microsoft Azure Synapse Analytics experience is essential. (Dedicated SQL Pool, Azure Data Factory, AzureStorage)
- Excellent communication skills with the ability to work within a team, across the business, and build strong relationships.
- End-to-end Data Warehouse experience: ingestion, ETL, big data pipelines, data architecture message queuing, stream processing, BI/Reporting, and Data Security.
- Ability to build processes supporting data transformation, data structures, metadata, dependency, and workload management, as well as the ability to manipulate,process, and extract value from large, disconnected structured and unstructureddatasets.
- Advanced SQL/relational database knowledge (including SSIS), query authoring (SQL).
- Experience performing root cause analysis on data, answering specific businessquestions, and identifying opportunities for improvement.
- Understanding of machine learning and artificial intelligence ML libraries and frameworks (TensorFlow, Spark, etc).
- Experience with Data Governance (Quality, Lineage, Data dictionary, and Security).
- Proficiency in programming language such as Python or equivalent for data engineering tasks.
- Familiarity with Git for version control and Azure DevOps for continuous integration and continuous deployment (CI/CD) processes.
