Lead Analyst, Data Platform Engineering

United Rentals

About The Position

The Lead Analyst, Data Platform Engineering serves as a Snowflake administrator and data pipeline engineer, responsible for the day-to-day security, performance, and reliability of United Rentals’ Snowflake platform. The role designs and builds pipelines that ingest data from diverse sources and develops curated, agent-ready data layers supporting the enterprise BI and AI ecosystem. It also supports AI applications such as Claude and ChatGPT by configuring and monitoring agents, building semantic views, and managing data shares between Snowflake accounts. The role activates and tests Snowflake Private Preview capabilities and helps bring useful new capabilities into production. The position supports Snowflake platform administration, data ingestion and transformation, AI and agent enablement, curated data and semantic views, organizational training and documentation, and strategic prioritization. It acts as a go-to resource for Snowflake capabilities and best practices, while balancing immediate business needs with longer-term priorities and following through on commitments.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or a related technical field.
At least 5 years of experience in database/platform administration, data engineering, or business intelligence, including at least 1 year administering Snowflake or a similar cloud data platform in production.
At least 1 year leading complex projects or initiatives.
Hands-on experience with a multi-account Snowflake architecture.
Strong SQL programming skills.
Experience with data ingestion and ETL/ELT tools, such as Fivetran/HVR, Matillion, dbt, Coalesce, or Postman.
Familiarity with AI/LLM enablement and tools such as Claude, ChatGPT, Microsoft Copilot, GitHub Copilot, or Snowflake Cortex Code.
Familiarity with agile development practices.
Strong analytical and critical-thinking skills, with a focus on practical problem-solving within constraints.
Strong technical documentation skills.
Excellent oral and written communication skills and ability to work collaboratively across IT and business teams.

Nice To Haves

Master’s degree.
Experience with BI and visualization tools such as Tableau or Sigma.
Understanding of agentic architectures, including MCP servers and agent-to-agent communication.
Snowflake certification, such as SnowPro Core or Advanced.

Responsibilities

Administer United Rentals’ Snowflake Discovery accounts, including users, roles, warehouses, RBAC/RLS/CLS, security policies, and account-level configurations.
Monitor Snowflake platform health, performance, and cost; tune workloads to meet business SLAs.
Audit and remediate security issues.
Manage availability between Snowflake accounts and partner platforms, including cloud and on-premises platforms.
Activate, test, and evaluate Snowflake Private Preview capabilities; document findings and recommend adoption strategies.
Design, build, and maintain data pipelines ingesting data from internal and external sources using replication, APIs, custom scripts, batch processing, and file-based loads.
Build and maintain transformation workflows across Foundation, Processed, and Curated enterprise data warehouse layers.
Monitor pipeline and job performance, troubleshoot failures, and resolve data quality and timeliness issues.
Partner with source system owners and corporate teams to onboard data sources and define ingestion standards.
Document pipeline designs, dependencies, and data lineage for governance and troubleshooting.
Support enablement, testing, and rollout of AI applications and copilots across the analytics organization.
Set up, configure, and monitor AI agents, including MCP server-based agent-to-agent integrations.
Collaborate with the data architecture team on ontology and knowledge graph context-layer efforts.
Build and maintain curated datasets and business data models for dashboards, semantic views, and downstream agents.
Design and maintain Semantic Views for Cortex Analyst and other AI/BI consumption layers.
Partner with BI and analytics teams using Sigma and Tableau to meet reporting and self-service needs.
Review data for accuracy and production readiness before release to business users and agents.
Serve as a resource for Snowflake capabilities, feature adoption, and platform best practices.
Document platform architecture, runbooks, and how-to guides; train team members and business users on relevant tools and capabilities.
Translate business requests into actionable priorities, balance short- and long-term demands, resolve or escalate issues appropriately, and support continuous learning and improvement.