Principal Solution Architect

Posted about 3 hours agoViewed
United States, Latin America, IndiaFull-TimeData Stack
Location:United States, Latin America, India
Languages:English
Seniority level:Principal
Skills:
AWSLeadershipProject ManagementPythonSQLApache AirflowCloud ComputingKafkaMicrosoft AzureSnowflakeSoftware ArchitectureData engineeringCI/CDProblem SolvingMentoringDevOpsTerraformTroubleshootingClient relationship managementData modeling
Requirements:
Advanced Data Platform expertise (Snowflake, AWS, Azure, Databricks). Extensive experience in architectural and operational guidance for cloud-native data warehouses. Production experience with Cloud and Distributed Data Storage technologies. Production experience with Data integration technologies. Production experience with Workflow Management and Orchestration. Strong working knowledge of SQL and ability to optimize queries. Deep expertise with cloud-native data technologies in AWS or Azure. Extensive experience with infrastructure as code using Terraform or CloudFormation. Experience building automated solutions using Python or similar. Well-versed with CI/CD frameworks and tools. Professional track record of creating, challenging, and improving processes. Unmatched troubleshooting and performance tuning skills. Proven experience as a technical team lead and mentor. Passion for learning new technology stacks and up-skilling team members. Ability to create and deliver detailed technical presentations for an executive audience. Excellent client-facing written and verbal communication skills.
Responsibilities:
Propose, design, and provision cloud-native data solutions on AWS/Azure. Leverage deep understanding of various data platform services and tools. Lead a technical team operating and managing modern data platforms. Provide clear ownership of multiple customer accounts as the technical leader. Navigate complex customer environments and mature their data platforms. Delegate to and coach Engineers for successful delivery. Provide thought leadership by recommending technologies and approaches. Lead discussions and contribute to data model design for Data Warehouses and Data Lakes. Automate, optimize, and expand customers’ data platforms and service offerings.
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