Director, Enterprise Data & Analytics

Pacsun Careers•Anaheim, CA

About The Position

The Director, Enterprise Data & Analytics is a hands-on technical and business leader accountable for Pacsun’s enterprise data platform, data warehouse, data engineering, data integrity, and analytics capabilities. The Director owns the strategy and day-to-day health of Pacsun’s Snowflake-based retail data ecosystem, ensuring data across stores, digital and social commerce, merchandising, planning, inventory, supply chain, finance, customer, and marketing is trusted, timely, scalable, and actionable, including for real-time and near-real-time use cases. The role partners directly with executives and business leaders to translate retail priorities into data solutions that improve sales, margin, inventory productivity, and customer experience, and leads the analytics organization and Strategy (formerly MicroStrategy) reporting environment. This is not a purely managerial role. The Director is expected to work hands-on in data engineering, modeling, integration, troubleshooting, and data-quality resolution. The role also evaluates and integrates AI capabilities into the data and analytics ecosystem, with appropriate governance and security. The Director defines and executes enterprise data and analytics strategy, architecture, roadmap, standards, and operating model; owns the Snowflake warehouse and associated pipelines, models, semantic layers, and data services; and leads real-time data integration, governance, analytics, reporting, and KPI standardization. The role partners with leaders across merchandising, planning, retail operations, eCommerce, marketing, supply chain, and finance; develops a small, high-performing organization; manages vendors, partners, resources, budgets, and licensing; and aligns data strategy with ERP and financial systems transformation. The position operates in a professional office environment using standard office equipment. Occasional evening or weekend work may be required during high-volume periods, and travel may be required. The role is full-time.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Engineering, or a related field, or equivalent practical experience.
10+ years of progressive experience in enterprise data, data engineering, data warehousing, analytics, or business intelligence, including at least 5 years of leadership responsibility.
Deep hands-on expertise with Snowflake and modern cloud data warehouse architecture, including performance, scalability, data modeling, and cost optimization.
Strong hands-on SQL, relational database, ETL/ELT, data integration, dimensional modeling, and enterprise data architecture experience, with a thorough understanding of data warehouse technology.
Substantial retail experience, preferably in fashion, apparel, or specialty retail, with a strong understanding of sales, inventory, cost, margin, merchandising, stores, eCommerce, and omnichannel operations.
Working knowledge of Strategy (formerly MicroStrategy) and enterprise BI platforms.
Demonstrated experience delivering real-time or near-real-time data integration, such as APIs, event streaming, change data capture, or MuleSoft.
Demonstrated experience establishing data quality, reconciliation, lineage, governance, security, and trusted KPI definitions.
Demonstrated record of learning, adopting, and integrating AI solutions into data and analytics work.
Proven ability to partner with executives and senior business leaders and translate business objectives into data strategy, technical solutions, and actionable insights.
Ability to operate as a hands-on technical leader rather than solely as a people manager, with excellent communication, influencing, and problem-solving skills.
Ability to operate with integrity, conduct, and confidentiality and to build cross-functional partnerships that support business results, transparency, collaboration, and accountability.
Ability to balance management presence with approachability and encourage associate feedback and interaction.

Nice To Haves

Experience with streaming, event-driven, or near-real-time data architectures.
Experience applying AI/ML, natural-language analytics, or agentic capabilities to enterprise data, and working knowledge of AI governance and data privacy.
Experience in a cloud-first retail technology environment with large-scale eCommerce and omnichannel data.
Experience supporting ERP and financial systems transformations.

Responsibilities

Define and execute the enterprise data and analytics strategy, architecture, roadmap, standards, and operating model, prioritizing initiatives by business value, feasibility, and ROI.
Own the Snowflake enterprise data warehouse and related pipelines, data models, semantic layers, and data services, including performance, scalability, security, and cost.
Remain hands-on by investigating data issues, reviewing and developing SQL and data transformations, optimizing pipelines and models, troubleshooting production problems, and resolving complex data-integrity issues.
Ensure data from Microsoft D365, Manhattan OMS and POS, eCommerce, and other source systems is accurate, complete, consistent, secure, and governed.
Establish data ownership, controls, monitoring, reconciliation, lineage, quality standards, and service levels for critical data and KPIs.
Lead real-time and near-real-time data integration using approaches such as APIs, event streaming, change data capture, and MuleSoft to support inventory, order, and sales visibility.
Lead executive dashboards, operational reporting, self-service analytics, and KPI standardization; oversee the Strategy (formerly MicroStrategy) environment, including its semantic layer, security, performance, upgrades, and licensing.
Partner with executives and leaders across merchandising, planning, retail operations, eCommerce, marketing, supply chain, and finance to identify opportunities and turn data into actionable recommendations.
Serve as the escalation point for data issues and communicate complex topics clearly to business and technical audiences.
Use retail data to identify opportunities to improve sales, margin, inventory turns, sell-through, allocation, fulfillment, and customer engagement.
Evaluate, pilot, and integrate AI capabilities where they deliver measurable value; establish responsible AI, privacy, and output-accuracy practices; prepare data for AI and machine learning use cases; and track emerging technology trends.
Lead and develop a small, high-performing organization, including a Data Architect and analytics and reporting leadership.
Manage third-party vendors, consulting partners, contract or offshore resources, data platform budgets, and licensing.
Maintain architecture and governance documentation, including data models, lineage, data flow diagrams, and a KPI glossary.
Align data strategy with Pacsun’s ERP and financial systems transformation to ensure data and reporting continuity.
Model integrity, transparency, collaboration, accountability, and company culture; develop talent and encourage associate feedback.
Recruit, identify, develop, and retain talent, and serve as a Pacsun advocate in the industry and marketplace.