Associate Director, Forecasting Data

Associate Director, Forecasting Data

Role Overview

The Data Leader – Forecasting will be responsible for building and governing high-quality, AI-ready data foundations to enable forecasting at scale. This role will drive the creation of certified data products and ensure data reliability, consistency, and accessibility across the enterprise.

Key Responsibilities

Data Strategy & Architecture

• Define the data strategy for forecasting (demand, supply, inventory, pricing, external signals)
• Design scalable data architecture on cloud platforms (e.g., GCP lakehouse)
• Standardize data models and semantic layers across regions

Data Product Development

• Build and own certified data products (forecast inputs, demand signals, master data)
• Define SLAs, quality metrics, and certification standards
• Enable self-service consumption for AI models and business users

Data Governance & Quality

• Establish governance frameworks (ownership, lineage, cataloging, access control)
• Ensure data quality, consistency, and completeness across multiple ERPs
• Drive data readiness for AI use cases

Integration & Platform Enablement

• Lead data ingestion and integration from internal systems and external sources
• Collaborate with platform teams on pipelines, transformations, and storage
• Ensure scalability and performance of data pipelines

Stakeholder Collaboration

• Partner with AI teams, business stakeholders, and IT teams
• Act as the bridge between business data needs and technical implementation
• Drive data literacy and adoption across teams

Key Skills & Qualifications

• 10–15 years in data engineering, data architecture, or data platforms
• Strong experience with cloud data platforms (GCP, Snowflake, Databricks)
• Expertise in data modeling, ETL/ELT, and data governance
• Experience working in multi-ERP, complex enterprise environments
• Strong stakeholder management and communication skills

Success Metrics

• Number of certified data products created
• Data quality scores (accuracy, completeness, timeliness)
• Time to enable new AI use cases
• Reduction in data-related issues/escalations

Pay Range: