Job Description

Job Summary:

The St. Louis Cardinals are looking for a Cloud Engineer to join our St. Louis-based Baseball Development team. Candidates should either live in, or be willing to relocate to, the St. Louis metro area. Candidates should also have a deep love of baseball, like the idea of being on a small, dynamic team with high individual flexibility and responsibility, and be competitively driven with a growth mindset. We compete with other teams in our domain just like our MLB players compete with other teams on the field. This position must have open flexibility during the season with hours and availability.

Job Duties:

The role of Cloud Engineer will be a cross-functional role that balances Google Cloud Platform systems engineering with software engineering and data engineering. Some example projects this position would be working on:

• Profiling a BigQuery procedure to determine a way to improve performance and reduce costs
• Writing a tool in Go to automate some common data engineering task
• Assessing options to improve resource utilization in a Kubernetes cluster
• Extending our Python ETL framework to support a new data source
• Planning, testing, and upgrading a database server to the latest version

Other essential job functions include:

• Maintain a small number of hosted servers/services: Google Composer, Google Kubernetes Engine, Cloud SQL (PostgreSQL)
• Diligently monitor cloud performance and cost
• Maintain a self-managed Microsoft SQL database server

Experience Required:

• Advanced knowledge of Google Cloud Platform offerings and best practices
• Intermediate knowledge of either Go or Python or two other programming languages
• Intermediate knowledge of Terraform or equivalent
• Growth mindset, self-motivated, curious, competitive, collaborative
• Curious to help wherever well suited to do so, across the full data stack, from ingestion, to modeling, to analysis, to visualization
• Knowledge of cloud networking best practices, VPC network peering, etc. helpful but not required
• Knowledge of database administration, query profiling, etc. helpful but not required
• Knowledge of data lifecycle processes with an emphasis more on accessibility and quality helpful but not required

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