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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # URBN Senior Data Engineer - **Company:** Urbn Inc. - **Location:** Philadelphia, PA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, ARM Architecture, BigQuery, Cloud Computing, Cloud Engineering, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Structures, Data Warehousing, Dimensional Modeling, Performance Tuning, Standard Sql, SQL Databases, Web Analytics, Google Cloud, Warehouse Management Systems, Cloud Platform System, Sql Optimization, Snowflake, Git, Git Flow, Google Bigquery, Software Version Control, Data Pipelines - **Published:** May 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=5ce9f597d2c97298 ## About the Role Do you have experience in Web analytics?, * Experience: At least 6-8 years of experience in data engineering, with a proven track record of modernizing data pipelines in cloud environments (Snowflake or BigQuery). * Modern Tooling: Proficiency in modern version control (Git) and CI/CD workflows. While we currently use Skybot for orchestration, familiarity with DAG-based tools (Airflow, Dagster, etc.) is a plus. * Advanced SQL: Expert-level SQL skills with the ability to write modular, performant code. Experience with modular SQL transformation pattern is highly preferred. * Domain Expertise: Previous experience with retail or e-commerce data models, specifically in web analytics pipelines and attribution logic. * Cloud Mastery: Deep hands-on experience with Snowflake (including telemetry and administrative functions) and/or Google Cloud Platform (BigQuery). * AI Literacy: Comfortable using AI assistants to optimize workflows and generate boilerplate code; ability to judge and audit AI-generated outputs for correctness. * Communication: Ability to explain complex technical migrations to stakeholders and collaborate effectively in a "team sport" modeling environment. ## Description URBN is seeking a Senior Data Engineer to join our Enterprise Data Warehouse (EDW) team during a pivotal phase of modernization. As we transition from legacy ETL frameworks to cloud-native architectures, we are looking for a builder who can bridge the gap between our established data foundations and the future of AI-augmented engineering. In this role, you will be a key player in modernizing our data pipelines, moving toward high-performance, modular code. You will collaborate with a deeply experienced team of engineers and managers to deliver complex projects across Marketing and Merchandising, ensuring our data ecosystem is scalable, observable, and ready for the next generation of retail analytics. Role Responsibilities: * Modernize & Migrate: Lead the technical refactoring of legacy data pipelines into modern, cloud-native pipelines within Snowflake and Google BigQuery. * Technical Standards: Establish and champion best practices for source control (Git), branching strategies, and CI/CD patterns within the Data Engineering team. * Pipeline Engineering: Design and implement robust data pipelines for merchandising, web analytics, multi-touch attribution (MTA), and customer journey mapping. * Operational Excellence & On-Call Support: Participate in a rotating on-call schedule to provide support for EDW Data Engineering owned assets and processes. Respond to alerts from Operations, troubleshoot and diagnose technical issues, coordinate with internal stakeholders and vendors, and manage escalations to ensure timely resolution. * AI-Augmented Development: Leverage AI coding assistants (e.g., Claude Code, Snowflake Cortex) to accelerate development, documentation, and the refactoring of legacy codebases. * Data Quality & Observability: Implement advanced Snowflake telemetry and data quality management functions to ensure pipeline reliability and proactive error detection. * Collaborative Modeling: Partner with Senior Engineers to implement "Modeling-as-Code," ensuring new data structures follow established dimensional modeling standards while remaining modular and testable. * Source Integration: Navigate complex integrations across a diverse source landscape, including Warehouse Management System, Sterling Order Management, Island Pacific Merchandising System, and POS systems. * Offshore Collaboration: Work closely with our offshore engineering partners to provide technical guidance and ensure consistency across global development efforts. ## Related Videos - [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) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Why Git Still Matters](https://www.wearedevelopers.com/videos/100288-why-git-still-matters) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)