Cloud Data Engineer, Professional Services, Google Public Sector

Google-posted 6 days ago
Full-time • Mid Level
Reston, VA
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As a Cloud Data Engineer, you will guide Public Sector customers to develop, configure and deploy their data and AI solutions. Together with the team, you will support customer implementations of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and more. You will consult with customers on how to best design their data and AI solutions including development and deployment of ML models, and integrations with leading Google technologies. You will travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to drive excellence in Google Cloud products and features. Your role requires the ability to travel up to 30% of the time.

  • Translate business requirements into conceptual, rational, and physical data models.
  • Be highly collaborative and work closely with data producers and data consumers across public sector customers and teams to understand the data needs, provide consultation, and align data solutions.
  • Analyze on-premise and cloud database environments, consulting on the optimal design for performance and deployment on Google Cloud Platform. Design, build, and maintain data warehouse and pipeline solutions.
  • Create and deliver best practices recommendations, tutorials, blog articles, sample code, and technical presentations, adapting to different levels of key business and technical stakeholders.
  • Travel regularly (up to 30%) for meetings, technical reviews, and onsite delivery activities.
  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 3 years of experience with relational database technologies such as PostgreSQL, MySQL, SQL Server, or Oracle.
  • Experience working with business stakeholders to understand requirements, provide technical leadership, and educate teams on GCP best practices.
  • Active, or the ability to obtain, a TS/SCI security clearance.
  • Experience with database and AI integrations.
  • Experience with database management tools for backups, recovery, snapshot management, sharding, partitioning and database performance tuning.
  • Experience in database administration techniques including storage, clustering, availability, disaster recovery, security, logging, performance tuning, monitoring and auditing.
  • Experience developing, deploying, and managing machine learning models, including experience writing software in one or more languages, such as Java, Python, or Golang.
  • Experience working with cloud databases such as RDS, Aurora, ElastiCache, CloudSQL, AlloyDB, Datastore or Bigtable.
  • Experience with machine learning operations (MLOps), data warehousing, and data pipeline development, including ETL and ELT.
  • bonus
  • equity
  • benefits
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