Data Engineer

Required Skills

• Bachelor s degree in a Technical Field: Computer Science, Data Science, Computational Finance, Statistics, Economics and/or Mathematics: Masters Preferred
• 5+ years of experience in data solution, pipeline, mart and/or warehouse development and delivery using agile development methodology
• Critical thinking skills to propose solutions, test, and make them a reality.
• 2+ years of experience in a Data Engineering Competency on a public cloud - Google, MS Azure, AWS
• 2+ years Integration and Configuration Scripting in Tekton and Terraform
• 3+ years of experience writing complex SQL
• 3+ years of experience writing data solutions in Python, Java, Scala or Go
• Deep understanding of data service ecosystems including data warehouses, lakes, metadata, meshes, fabrics and analytical use cases
• User experience advocacy through empathetic stakeholder relationship
• Excellent Communication Skills, Verbal and Written, for both internal and external team members

• Bachelor s degree in a Technical Field: Computer Science, Data Science, Computational Finance, Statistics, Economics and/or Mathematics: Masters Preferred
• 5+ years of experience in data solution, pipeline, mart and/or warehouse development and delivery using agile development methodology
• Critical thinking skills to propose solutions, test, and make them a reality.
• 2+ years of experience in a Data Engineering Competency on a public cloud - Google, MS Azure, AWS
• 2+ years Integration and Configuration Scripting in Tekton and Terraform
• 3+ years of experience writing complex SQL
• 3+ years of experience writing data solutions in Python, Java, Scala or Go
• Deep understanding of data service ecosystems including data warehouses, lakes, metadata, meshes, fabrics and analytical use cases
• User experience advocacy through empathetic stakeholder relationship
• Excellent Communication Skills, Verbal and Written, for both internal and external team members

• Design, Develop and Implement data engineering solutions using standards, templates, patterns and best practices in the Google Cloud Platform
  • Full stack data engineering solutions utilizing both structured and unstructured data: development, ingestion, curation, implementation, deployment, automation and monitoring
  • Collaborates with the Data Factory Engineering Organization, Data Architecture, PEM, GDIA, Information Technology and Data Consumers to drive data engineering capabilities, product design and proof of concepts, MVPs, to expand understanding, define technical optimization, explore configurations and overcome challenges
  • Create high quality, elegant data engineering solutions that focus on cloud-first, encapsulation, repeatability, automation and auditability
  • Work as an individual contributor and part of a team to build, test, maintain and troubleshoot data solutions
• Continuously integrates and deploys data solutions via CI/CD
• Use of Test Driven Development and Code Pairing Practices