Procurement Analytics, Data Infrastructure and Data Products Manager

Delta Air Lines, Inc.; Atlanta, Northern (GA, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Delta Air Lines, Inc. is seeking a Procurement Analytics, Data Infrastructure & Data Products Manager to design, build, and evolve analytics platforms and data products for procurement and supply chain.

You will partner with Finance, IT, and Operations to translate complex data into actionable insights. This hands-on role balances data architecture, BI engineering, and business acumen to drive sourcing strategies, supplier performance, and enterprise cost optimization through scalable data

Qualifications

• Hands-on builder with data platform experience.
• Experience delivering dashboards and analytics products.
• Proven ability to translate procurement data into insights.

Responsibilities

• Design, build, and maintain end-to-end data infrastructure.
• Develop analytical cubes for supplier, category, contract, and spend.
• Partner with Finance to align analytics to budgets and savings.
• Create executive-ready dashboards in Power BI or Tableau.
• Lead offshore analytics teams and define data pipelines.

Skills

Data architecture

BI engineering

Financial acumen

Product mindset

Stakeholder management

Tools

Power BI

Tableau

Job description

The Procurement Analytics, Data Infrastructure & Data Products Manager will design, build, and evolve analytics platforms, data products, and master data foundations that support the Procurement and Supply Chain organization. This role partners closely with Strategic Sourcing, Finance, Operations, and IT to enable fact-based decisions through scalable data models, spend cubes, dashboards, and curated analytics products across Direct and Indirect spend.

This role is designed for a hands-on builder with a strong product mindset, combining data architecture, BI engineering, and financial acumen to translate complex procurement data into actionable insights that drive sourcing strategies, supplier performance, and enterprise cost optimization.

Key Responsibilities

Procurement Data Infrastructure & Architecture

• Design, build, and maintain end-to-end data infrastructure including ingestion, transformation, modeling, and semantic layers.
• Develop analytical cubes covering supplier, category, contract, volume, rate, and spend hierarchies.
• Integrate contracts, purchase orders, invoices, finance actuals, and operational data into a single source of truth.
• Establish governance and quality standards for supplier master, category hierarchies, and contract/rate data.

Spend, Financial & Should-Cost Analytics

• Partner with Finance to align analytics to budgets, forecasts, P&L impacts, and savings baselines.
• Deliver volume, rate, mix, price variance, and Total Cost of Ownership (TCO) analytics.
• Connect negotiated rates and should-cost assumptions to actual spend to identify leakage and compliance gaps.

Reporting, Dashboards & Self-Service Enablement

• Build scalable dashboards and reporting solutions (Power BI / Tableau) delivering executive-ready insights.
• Develop intuitive, self-service analytics products embedded into regular business rhythms.
• Translate complex datasets into clear, decision-oriented narratives for leadership.

Offshore Analytics & Data Engineering Partnership (Dotted-Line)

• Provide functional (dotted-line) leadership to offshore analytics and data engineering teams supporting Procurement analytics.
• Translate business requirements into clear technical direction, reviewing deliverables to ensure quality, scalability, and alignment to standards.
• Leverage offshore capacity to accelerate delivery while retaining hands-on ownership of solution design and analytics outcomes.
• Define and govern the ETL / ELT architecture and data pipeline requirements, including source integration, transformations, orchestration, and data quality controls, while providing functional (dotted‑line) direction to offshore teams responsible for building and maintaining the pipelines.

Product Ownership & Enablement

• Act as analytics product owner by defining use cases, maintaining delivery roadmaps, and prioritizing enhancements based on business value.
• Enable adoption through structured trainings, equipping category teams to self‑serve analytics by delivering hands‑on training, practical playbooks, and by embedding data products into core operating rhythms.

Future-Ready Data Foundation

• Design AI-ready data structures and semantic layers enabling future ML, AI, and LLM-based procurement use cases.
• Partner with IT and engineering teams on scalable, enterprise-grade cloud data architecture.