Quick Overview
Job Description
Job Title | Data Engineer (Snowflake) |
Location | Hybrid 3 days onsite Tue-Thur, in Dublin, CA Need nearby candidates |
Type | C2C |
Visa | USC |
Duration | 6 Months |
Interview Mode | video 2-3 rounds |
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Work Authorization (open to ISS/C2C) No Sponsorship Available Interview Process • 1st Round - 45 min, w/ Manager , techno-functional • 2nd Round - 60 min, w/Lead + Sr. Engineer - Technical Deep Dive • 3rd Round - 45 min, w/POC -
Hands-on Snowflake data engineer with strong Azure, Python, and SQL skills who can build working prototypes, troubleshoot complex platform issues, and evaluate new technologies independently.
Reason for position Support and evolve our existing Snowflake/Azure data platform while evaluating and building new data and AI capabilities. The role combines hands-on engineering, platform troubleshooting, research, prototyping, and emerging technology adoption. Team Overview Enterprise data technology team supporting our modern cloud data environment.
The role partners across Data Engineering, Analytics, Architecture, Infrastructure, and related technical teams.
This is not a dedicated production-support role. The engineer will help troubleshoot platform issues and provide broader L2/L3-type technical support when needed, including occasional issues outside normal hours.
Work split: ~60% Innovation / new capabilities ~40% Existing platform / support
The team is continuing to evolve its data platform while exploring new technologies, including AI capabilities, Snowflake Cortex, agents, Apache Iceberg, and automation Project Description Support, enhance, and evolve the enterprise data platform, with a primary focus on Snowflake, Azure, Python, and SQL. The position combines traditional data platform engineering with substantial innovation and POC work.
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
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
o 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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