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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Analyst, Data Platform Engineering - **Company:** United Rentals - **Location:** Stamford, CT, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, ARM Architecture, Information Systems, Computer Programming, Databases, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Visualization, Data Warehousing, Graph Database, Role-Based Access Control, Tableau (Software), Scripting, Data Ingestion, Postman, Microsoft Power Automate, GitHub Copilot, Large Language Models, Snowflake, Data Layers, Information Technology, Data Lineage, Data Analytics, Api Design, GPT, Data Pipelines - **Published:** August 10, 2026 - **Apply:** https://dejobs.org/x/x/21F9B79D23FA4C349B9F0FE630EF4BDD/job/ ## About the Role * Bachelor's Degree in Computer Science, Information Systems, or a related technical field, with a Master's Degree preferred * 5+ years of experience in data engineering, database/platform administration, or business intelligence, including at least 1 year with hands-on experience administering Snowflake or a similar cloud data platform in a production environment * Hands-on experience with a multi-account Snowflake architecture * Strong SQL programming skills * Experience with data ingestion and ETL/ELT tools, e.g. Fivetran/HVR, Matillion, dbt, Coalesce, Postman * Familiarity with AI/LLM enablement and tools such as Claude, ChatGPT, Microsoft Copilot, Github Copilot, Snowflake Cortex Code * Experience with BI and visualization tools like Tableau or Sigma is a plus * Understanding of agentic architectures, including MCP servers and agent-to-agent communication, is a plus * Snowflake certification (SnowPro Core or Advanced) a strong plus * Familiarity with agile development practices * Strong analytical and critical thinking skills with a focus on practical problem-solving within constraints * Strong technical documentation skills * Must have excellent oral and written communication skills to work collaboratively and cross-functionally with IT and business leads daily ## Description The Senior Analyst, Data Platform Engineering serves as the team's primary Snowflake administrator and data pipeline engineer, responsible for the day-to-day security, performance, and reliability of United Rentals' Snowflake platform. This role designs and builds data pipelines that ingest data from a wide variety of sources, and develops the curated, agent-ready data layers that power the enterprise's BI and AI ecosystem. The Senior Analyst plays a lead role in enabling AI applications such as Claude and ChatGPT across the organization, including configuring and monitoring AI agents, building semantic views, and managing data shares between Snowflake accounts. This person is also responsible for activating and testing Snowflake Private Preview capabilities, helping the team stay ahead of platform innovation and bringing new capabilities into production. What you'll do: * Snowflake Platform Administration * Serves as the primary Snowflake administrator for URI's Discovery accounts; managing users, roles, warehouses, RBAC / RLS / CLS, security policies, and other account-level configurations. * Monitors platform health, performance and cost, tuning workloads as needed to meet business SLAs. * Audits and remediates security issues. * Manages availability between Snowflake accounts and partner platforms, whether cloud or on-prem. * Activates, tests, and evaluates Snowflake Private Preview capabilities (e.g., Agent / CoWork / Semantic enhancements, new ingestion or compute features, etc.) ahead of general availability, documenting findings and recommending adoption strategies. * Data Pipeline & Ingestion Engineering * Designs, builds, and maintains data pipelines that ingest data from a variety of internal and external sources using multiple techniques including CDC / mirror replication, API-based ingestion, custom scripts, and traditional batch and file-based loads. * Builds and maintains transformation workflows across the Foundation, Processed, and Curated layers of the enterprise data warehouse. * Monitors pipeline and job performance, troubleshoots failures, and resolves data quality or timeliness issues. * Partners with source system owners and corporate teams to onboard new data sources and define ingestion standards. * Documents pipeline design, dependencies, and data lineage to support governance and troubleshooting. * AI & Agent Enablement * Supports enablement, testing, and rollout of AI applications and copilots (e.g., Claude, ChatGPT/Copilot, Snowflake Cortex Agents) across the analytics organization. * Helps set up, configure, and monitor agents (e.g., Executive Agent, BI Agent, Ontology Agent), including MCP server-based agent-to-agent integrations. * Partners with the broader data architecture team on context-layer efforts (ontology, knowledge graph) so agents can reliably query curated business data. * Curate Data & Semantic Views * Builds and maintains curated data sets and business data models that feed dashboards, semantic views, and downstream agents. * Designs and maintains Semantic Views that support Cortex Analyst and other AI/BI consumption layers. * Partners with BI and analytics teams (Sigma, Tableau) to ensure the curated layer meets reporting and self-service needs. * Reviews data for accuracy and production-readiness prior to release to business users and agents. * Organizational Support & Enablement * Acts as a go-to resource across the Data & Analytics team for Snowflake capabilities, new feature adoption, and platform best practices. * Documents platform architecture, runbooks, and how-to guides for the team and business users. * Trains team members and business users on new tools, features, and capabilities relevant to their needs. ## Related Videos - [Are Your APIs Ready for AI Agents](https://www.wearedevelopers.com/videos/2004-are-your-apis-ready-for-ai-agents) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)