Associate Director, Data Intelligence

Team Leadership & Operations

Lead, mentor, and develop a team of data engineers, analysts, integration engineers, PowerBI developers and AI/ML Engineers.

Provide direction, coaching, and performance feedback to team members while supporting their career growth and technical development.

Foster a culture of continuous improvement, collaboration, and innovation.

Implement and maintain a comprehensive data strategy aligned with business goals.

Manage intake, prioritization, and delivery of data-related requests, projects, and enhancements

Establish SLAs, operational metrics, and reporting cadences to communicate team performance to leadership

Manage resource planning, workload distribution, project delivery, hiring, onboarding and support activities across the data intelligence function

Foster a collaborative, data-driven culture aligned with organizational goals and values

Partner closely with cross-functional teams including ecommerce, Data Engineering, Business Insights, Enterprise Applications, Infrastructure, Security, and QA.

Provide status updates to leadership on operational health, key issues, risks, priorities, and progress

Data Warehouse Management

Oversee the design, development, and operational maintenance of the enterprise Data Warehouse architecture

Manage data ingestion pipelines, ETL/ELT processes, and data transformation workflows

Ensure data integrity, consistency, and availability across all warehouse environments (Dev, QA, Prod)

Provide technical leadership in SQL development, ETL/ELT processes, data modeling, database design, and performance tuning.

Evaluate and recommend new technologies, tools, and methodologies to enhance warehouse performance

Support data warehouse enhancements, new data source onboarding, reporting needs, and business-critical data initiatives.

Implement and enforce data quality controls, lineage, metadata management, and documentation.

API Integrations

Lead the execution of API integrations connecting internal and third-party systems

Collaborate with engineering and vendor teams to design, build, and monitor RESTful and SOAP API integrations

Establish standards for API documentation, versioning, error handling, and data validation

Drive improvements in integration support processes, incident response, and operational reliability.

Partner with application, integration, ERP, ecommerce, and business teams to ensure APIs and data integrations are stable and functioning as expected.

Assist to troubleshoot and resolve integration failures, ensuring minimal disruption to downstream systems and reporting

Analytics & Power BI

Manage and support analytics requests related to Power BI reports, dashboards, datasets, and business reporting needs.

Partner with business users to understand reporting requirements, data definitions, KPI needs, and analytics priorities.

Champion self-service analytics by establishing best practices, data models, and certified datasets

Provide training and enablement resources to empower business users across the organization

Support report enhancements, dashboard issue resolution, and dataset refresh failures.

Promote consistency in reporting, data definitions, and analytics best practices across the organization.

Data Governance & Security

Lead the overall data intelligence strategy aligned with business priorities, technology roadmap, and enterprise goals.

Partner with Security, Compliance, and Business teams to enforce data governance policies and access controls

Ensure compliance with applicable data privacy regulations (e.g., GDPR, CCPA) and SOX/ITGC controls where applicable

Manage audit readiness, change management, and segregation of duties across environments.

Maintain comprehensive data dictionaries, lineage documentation, data cataloging, and metadata management practices

AI & Machine Learning

Lead and support the organization’s advancement into AI, machine learning, predictive analytics, and intelligent automation.

Identify practical AI/ML use cases that can improve business outcomes, operational efficiency, customer experience, and decision-making.

Partner with data scientists, engineers, analysts, and business teams to develop scalable AI/ML solutions.

Help establish the foundation required for AI readiness, including clean data pipelines, governed datasets, quality controls, and reusable data assets.

Support the evaluation and implementation of AI-enabled analytics tools, machine learning platforms, and automation capabilities.

Promote responsible AI practices, including data privacy, model transparency, risk management, and ethical use of data.