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<table style="border-collapse:collapse;" border="0" cellpadding="0" cellspacing="0" width="396pt"><tbody><tr style="height:409.5pt;" height="546"><td class="xl63" style="height:409.5pt;width:396pt;" height="546" width="527">Cloud Data Architect&nbsp; Role: T0 The ideal professional for this Cloud Architect role will: ● Have a passion for design, technology, analysis, collaboration, agility, and planning, along with a drive for continuous improvement and innovation. ● Exhibit expertise in managing high-volume data projects that leverage Cloud Platforms, Data Warehouse reporting and BI Tools, and the development of relational databases. ● Research, identify, and internally market enabling data management technologies based on business and end-user requirements. ● Seek ways to apply new technology to business processes with a focus on modernizing the approach to data management. ● Consult with technical subject matter experts and develop alternative technical solutions. Advise on options, risks, costs versus benefits, and impact on other business processes and system priorities. ● Demonstrate strong technical leadership skills and the ability to mentor others in related technologies. Qualifications • Bachelor's degree in a computer-related field or equivalent professional experience is required. • Preferred master’s degree in computer science, information systems or related discipline, or equivalent and extensive related project experience. • 10+ years of hands-on software development experience building data platforms with tools and technologies such as Hadoop, Cloudera, Spark, Kafka, Relational SQL, NoSQL databases, and data pipeline/workflow management tools. • 6+ years of experience working with various cloud platforms (at least two from among AWS, Azure &amp; GCP). • Experience in multi-cloud data platform migration and hands-on experience working with AWS, AZURE / GCP • Experience in Data &amp; Analytics projects is a must. • Data modeling experience – relational and dimensional with consumption requirements (reporting, dashboarding, and analytics). • Thorough understanding and application of AWS services related to Cloud data platform and Datalake implementation – S3 Datalake, AWS EMR, AWS Glue, Amazon Redshift, AWS Lambda, and Step functions with file formats such as Parquet, Avro, and Iceberg. • Must know the key tenets of architecting and designing solutions on AWS and Azure Clouds. • Expertise and implementation experience in data-specific areas, such as AWS Data Lake, Data Lakehouse Architecture, and Azure Synapse and SQL Datawarehouse. • Apply technical knowledge to architect and design solutions that meet business and IT needs, create Data &amp; Analytics roadmaps, drive POCs and MVPs, and ensure the long-term technical viability of new deployments, infusing key Data &amp; Analytics technologies where applicable. • Be the Voice of the Customer to share insights and best practices, connect with the Engineering team to remove key blockers, and drive migration solutions and implementations. • Familiarity with tools like DBT, Airflow, and data test automation. • MUST have experience with Python/PySpark/Scala in Big Data environments. • Strong skills in SQL queries in Big Data tools such as Hive, Impala, Presto. • Experience working with and extracting value from large, disconnected, and/or unstructured datasets. • Demonstrated ability to build processes that support data transformation, data structures, metadata, dependency, and workload management. • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), and working familiarity with a variety of databases. • Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.</td></tr></tbody></table><table style="border-collapse:collapse;" border="0" cellpadding="0" cellspacing="0" width="605pt"><tbody><tr style="height:409.5pt;" height="546"><td class="xl63" style="height:409.5pt;width:605pt;" height="546" width="806">&nbsp;</td></tr></tbody></table>

<table style="border-collapse:collapse;" border="0" cellpadding="0" cellspacing="0" width="605pt"><tbody><tr style="height:409.5pt;" height="546"><td class="xl63" style="height:409.5pt;width:605pt;" height="546" width="806"><table style="border-collapse:collapse;" border="0" cellpadding="0" cellspacing="0" width="396pt"><tbody><tr style="height:409.5pt;" height="546"><td class="xl63" style="height:409.5pt;width:396pt;" height="546" width="527">Cloud Data Architect&nbsp; Role: T0 The ideal professional for this Cloud Architect role will: ● Have a passion for design, technology, analysis, collaboration, agility, and planning, along with a drive for continuous improvement and innovation. ● Exhibit expertise in managing high-volume data projects that leverage Cloud Platforms, Data Warehouse reporting and BI Tools, and the development of relational databases. ● Research, identify, and internally market enabling data management technologies based on business and end-user requirements. ● Seek ways to apply new technology to business processes with a focus on modernizing the approach to data management. ● Consult with technical subject matter experts and develop alternative technical solutions. Advise on options, risks, costs versus benefits, and impact on other business processes and system priorities. ● Demonstrate strong technical leadership skills and the ability to mentor others in related technologies. Qualifications • Bachelor's degree in a computer-related field or equivalent professional experience is required. • Preferred master’s degree in computer science, information systems or related discipline, or equivalent and extensive related project experience. • 10+ years of hands-on software development experience building data platforms with tools and technologies such as Hadoop, Cloudera, Spark, Kafka, Relational SQL, NoSQL databases, and data pipeline/workflow management tools. • 6+ years of experience working with various cloud platforms (at least two from among AWS, Azure &amp; GCP). • Experience in multi-cloud data platform migration and hands-on experience working with AWS, AZURE / GCP • Experience in Data &amp; Analytics projects is a must. • Data modeling experience – relational and dimensional with consumption requirements (reporting, dashboarding, and analytics). • Thorough understanding and application of AWS services related to Cloud data platform and Datalake implementation – S3 Datalake, AWS EMR, AWS Glue, Amazon Redshift, AWS Lambda, and Step functions with file formats such as Parquet, Avro, and Iceberg. • Must know the key tenets of architecting and designing solutions on AWS and Azure Clouds. • Expertise and implementation experience in data-specific areas, such as AWS Data Lake, Data Lakehouse Architecture, and Azure Synapse and SQL Datawarehouse. • Apply technical knowledge to architect and design solutions that meet business and IT needs, create Data &amp; Analytics roadmaps, drive POCs and MVPs, and ensure the long-term technical viability of new deployments, infusing key Data &amp; Analytics technologies where applicable. • Be the Voice of the Customer to share insights and best practices, connect with the Engineering team to remove key blockers, and drive migration solutions and implementations. • Familiarity with tools like DBT, Airflow, and data test automation. • MUST have experience with Python/PySpark/Scala in Big Data environments. • Strong skills in SQL queries in Big Data tools such as Hive, Impala, Presto. • Experience working with and extracting value from large, disconnected, and/or unstructured datasets. • Demonstrated ability to build processes that support data transformation, data structures, metadata, dependency, and workload management. • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), and working familiarity with a variety of databases. • Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.</td></tr></tbody></table></td></tr></tbody></table>

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