Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Dublin, CA, United States
Posted
Yesterday
SQLETLSnowflakeApachePythonGenerative AIAzure
Job Description
The engineer will:
- Build and prototype new Snowflake capabilities
- Develop solutions using Python and SQL
- Research emerging data and AI technologies
- Build POCs to determine whether new capabilities should be adopted
- Experiment with AI/agent-based solutions
- Troubleshoot and optimize the existing Snowflake/Azure environment
- Improve platform performance, reliability, automation, and cost efficiency
- Help establish practical approaches for technologies where mature patterns may not yet exist
The ideal person is a builder + experimenter + data engineer, rather than someone focused primarily on traditional ETL development.
Duties/Day to Day Overview
- Approximately 60% innovation / 40% platform support
- Research and evaluate emerging Snowflake, cloud data, and AI capabilities
- Build rapid POCs and prototypes
- Develop hands-on solutions using Python, SQL, Snowflake, and Azure
- Experiment with Snowflake capabilities including potential AI/agent use cases
- Evaluate new technologies and develop recommendations for adoption
- Build within the Snowflake environment
- Investigate query history/plans, warehouse sizing, and performance issues
- Troubleshoot complex data/platform issues
- Participate in root-cause analysis and issue resolution
- Help optimize Snowflake performance and consumption
- Support platform automation and operational improvements
- Contribute to monitoring, observability, and platform reliability
- Collaborate across engineering, architecture, analytics, and infrastructure teams
- Occasionally assist with L2/L3-type production escalations
- Explore emerging architecture patterns including Apache Iceberg/open table formats
Top Requirements
(Must haves)
Experience Target
- Approximately 7+ years overall IT experience
- 5+ years working with data platforms
Snowflake
- 5+ years working with modern data platforms / strong Snowflake experience
- Hands-on Snowflake engineering and development
- Comfortable building solutions within Snowflake
- Strong enough platform knowledge to troubleshoot issues
- Understanding of warehouse sizing
- Query history / query plan troubleshooting
- Performance and optimization knowledge
Important: Candidate does not need to be a pure Snowflake Administrator. The preference is a builder/engineer with strong platform knowledge.
Azure
- Strong hands-on Azure experience
- Understands how data engineering solutions operate within the Azure ecosystem
- Azure is one of the hiring manager's top three skills
Python
- Strong hands-on Python development
- Must be able to build solutions, automation, and prototypes with Python
- Not sufficient to only have conceptual Python knowledge
- Python is one of the hiring manager's top three skills
SQL
- Strong hands-on SQL
- Query development/troubleshooting
- ·Stored-procedure-oriented data work
- Ability to use SQL for diagnostics and platform engineering
Builder / POC Mentality
Candidate must be comfortable:
- Researching unfamiliar technologies
- Prototyping new Snowflake capabilities
Building POCs
- Testing potential solutions against business/technical use cases
- Identifying limitations and trade-offs
- Developing a point of view on whether/how technology should be adopted
- Working through ambiguity without requiring established patterns
AI Exposure / Hands-On Interest
- Some hands-on AI experimentation desired
- Candidate does not need to be an AI/ML expert
- Preference for someone who has built or experimented with AI, rather than simply consumed tools such as ChatGPT/Copilot
- Interest in AI agents and AI-driven automation
- Ability to apply AI concepts within the Snowflake/data platform environment
Platform Troubleshooting
- Ability to troubleshoot Snowflake/data platform issues
- Performance investigation
- Root-cause analysis
- Production issue resolution
- Comfortable providing occasional L2/L3-type support
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