Director, Systems Integration & AI Analytics

Elantis; Anaheim (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Elantis seeks a hands‑on Director of Enterprise Data & Analytics to own the Snowflake data platform across stores, eCommerce, and planning. You will translate retail priorities into scalable data solutions, partner with execs, and lead data governance, security and AI initiatives.

This role requires deep technical leadership in data engineering, modeling, and analytics, while shaping the roadmap, governance, and cost optimization for a complex retail ecosystem.

Qualifications

• Bachelor’s degree in CS/IS/Data Eng or equivalent practical experience.
• 10+ years in enterprise data, data warehousing, analytics, or BI with at least 5 years in leadership.
• Deep hands‑on Snowflake expertise across performance, scalability, modeling, and cost optimization.
• Strong hands‑on SQL, relational DB, ETL/ELT, data integration, dimensional modeling, and enterprise architecture.
• Substantial retail experience with sales, margin, inventory, eCommerce, and omnichannel operations.
• Experience with Strategy (MicroStrategy) and enterprise BI.
• Experience delivering real‑time data integration via APIs, streaming, CDC, or MuleSoft.
• Proven ability to establish data quality, governance, and KPI definitions.
• Proven record of adopting AI solutions in data & analytics workflows.
• Ability to partner with executives and translate business objectives into data strategy and actionable insights.

Responsibilities

• Define and execute the enterprise data & analytics strategy, architecture, and roadmap.
• Own the Snowflake data warehouse, pipelines, models, and semantic layers for reporting and analytics.
• Hands‑on technical leadership: SQL, transformations, pipeline optimization, and data‑quality resolution.
• Ensure data integrity, governance, lineage, quality, security and SLAs across sources.
• Lead real‑time and near‑real‑time data integration using APIs, streaming, CDC, and MuleSoft.
• Provide analytics leadership for executive dashboards, reporting, self‑service analytics, KPI standardization.
• Partner with executives across merchandising, planning, retail ops, ecommerce, finance to turn data into insights.
• Drive AI adoption with responsible AI practices and governance; prepare data for AI/ML use cases.
• Manage a small team and vendors, budgets, and licensing; align with ERP/financial transformations.
• Document architecture & governance, data models, lineage, and data flows.

Skills

Snowflake

SQL

ETL/ELT

Data modeling

Data warehousing

Real-time data integration

AI/GenAI solutions

Leadership

Retail domain knowledge

Data governance

Education

Bachelor’s degree in Computer Science / Information Systems / Data Engineering

Tools

Snowflake

Strategy (MicroStrategy)

MuleSoft

Job description

The Director, Enterprise Data & Analytics, is a hands‑on technical and business leader accountable for Client’s enterprise data platform, data warehouse, data engineering, data integrity, and analytics capabilities. The Director owns the strategy and day-to‑day health of Client's Snowflake‑based retail data ecosystem, ensuring data across stores, digital commerce and social commerce, merchandising, planning, inventory, supply chain, finance, customer, and marketing is trusted, timely, scalable, and actionable, including real‑time and near‑real‑time use cases.

The Director partners directly with executive and business leaders to translate retail priorities into data solutions that improve sales, margin, inventory productivity, and customer experience, and leads the analytics organization, including the Strategy (formerly MicroStrategy) reporting environment. This is not a purely managerial role: the successful candidate must be willing and able to work hands‑on in data engineering, modeling, integration, troubleshooting, and data‑quality resolution. The Director is also a forward‑thinking leader who actively learns, adopts, and integrates AI solutions into the data and analytics ecosystem, with governance and security in place.

• Strategy and roadmap. Define and execute the enterprise data and analytics strategy, architecture, roadmap, standards, and operating model, prioritizing initiatives by business value, feasibility, and ROI.
• Data platform and architecture. Own the Snowflake enterprise data warehouse and the related pipelines, data models, semantic layers, and data services that support reporting and analytics, including performance, scalability, security, and cost.
• Hands‑on technical leadership. Stay technically hands‑on: investigate data issues, review and develop SQL and data transformations, optimize pipelines and models, troubleshoot production problems, and lead resolution of complex data‑integrity issues.
• Data integrity and governance. Ensure data from Microsoft D365, Manhattan OMS and POS, eCommerce, and other source systems is accurate, complete, consistent, secure, and well governed. Establish ownership, controls, monitoring, reconciliation, lineage, quality standards, and service levels for critical data and KPIs.
• Real‑time integration. Lead real‑time and near‑real‑time data integration into the enterprise platform, using approaches such as APIs, event streaming, change data capture, and MuleSoft, to support inventory, order, and sales visibility.
• Analytics and reporting leadership. Provide leadership for executive dashboards, operational reporting, self‑service analytics, and KPI standardization, and oversee the Strategy (formerly MicroStrategy) environment, including the semantic layer, security, performance, upgrades, and licensing.
• Executive and business partnership. Partner with executives and leaders in 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.
• Retail business impact. Build deep fashion and apparel retail knowledge and proactively identify opportunities to improve sales, margin, inventory turns, sell‑through, allocation, fulfillment, and customer engagement through data.
• AI adoption and responsible AI. Lead the evaluation, piloting, and integration of AI capabilities (e.g., natural language query, AI‑generated insights, anomaly detection, predictive analytics, Snowflake Cortex, and GenAI tools) 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 data, analytics, and retail technology trends.
• Team and partners. Lead and develop a small, high‑performing organization, including a Data Architect and analytics and reporting leadership. Manage third‑party vendors, consulting partners, and contract or offshore resources, along with data platform budgets and licensing.
• Documentation and ERP alignment. Maintain architecture and governance documentation, including data models, lineage, data flow diagrams, and a KPI glossary, and align data strategy with Client’s ERP and financial systems transformation to ensure data and reporting continuity.
• Exemplify integrity, transparency, and a collaborative spirit in all interactions.
• Cultivate cross‑functional partnerships with business and technology leaders to drive results and accountability.
• Lead talent development to build a high‑performing, AI‑literate team.
• Promote company culture, values, and norms while remaining approachable and encouraging feedback.

Education/Experience Required:

• 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.
• Mandatory: deep hands‑on expertise with Snowflake and modern cloud data warehouse architecture, including performance, scalability, data modeling, and cost optimization.
• Mandatory: 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.
• Mandatory: substantial retail experience, preferably 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 (e.g., 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.
• Demonstrated ability to operate as a hands‑on technical leader rather than solely as a people manager, with excellent communication, influencing, and problem‑solving skills.

Preferred Qualifications:

• 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.