Shelton - Data Engineering - Dir- Data Engineering

Schedule Full time

Job Type Permanent

Industry It and internet

At Subway, we are not standing still. We are building.

This is a business focused on what matters most: growing franchisee profitability, strengthening our brand and creating long-term value. The people who thrive here are the ones who want to make a real impact.

You will not just do the work. You will shape it.

We move fast. We think like owners. We make decisions that matter. We hold ourselves to a high standard because what we do directly impacts thousands of franchisees around the world.

If you bring energy, accountability and a bias for action, you will fit right in.

We take the work seriously, but we also know the best results come from teams that support each other, celebrate wins and show up ready to build something better every day.

This is your chance to be part of what’s next.

The Director, Data Engineering is responsible for leading the design, development, and operation of enterprise data engineering platforms and pipelines that support analytics, reporting, data products, and downstream consumption. This role owns delivery execution, reliability, and scalability of data systems while ensuring alignment with enterprise architecture, security, and governance standards. The Director leads data engineering teams and partners closely with Data Product, Analytics, Platform, and Security leaders to enable trusted, timely, and accessible data across the organization

Responsibilities include but not limited to:

• Own the design, development, and operations of Subway’s enterprise data engineering platform on AWS Databricks, including migration strategy from the existing Amazon Redshift environment.
• Lead the delivery of Medallion Architecture (Bronze / Silver / Gold) pipelines across all QSR domains - Restaurant, Sales, Inventory, Guest, Marketing, and Supply Chain.
• Oversee development of Delta Live Tables, batch and streaming pipelines, and feature engineering workflows across Databricks and Microsoft Fabric.
• Architect and deliver a self-service data platform leveraging Unity Catalog, RBAC/ABAC governance, and Delta/Iceberg interoperability to enable domain teams to independently build and consume trusted data products.
• Define and execute the platform migration roadmap - phasing workloads from Redshift to Databricks/Snowflake with minimal business disruption.
• Partner with the Enterprise Data & AI Architect to implement and evolve a Data Mesh architecture, enabling domain teams to own and publish certified data products.

• Drive adoption of Data Ops practices including CI/CD for data pipelines, automated testing, data contract enforcement, and pipeline observability.
• Ensure platform reliability, SLA adherence, and proactive incident management for all production data pipelines and data products.
• Implement infrastructure-as-code and environment management for Databricks work spaces, clusters, and job orchestration.
• Establish on‑call processes, runbooks, and escalation paths for Tier-1 data platform incidents, targeting ≤99.5% pipeline uptime.

• Define and enforce data quality standards and SLAs across all engineering pipelines and analytics products - partnering with the Data Governance function and Data Product Owners.
• Implement data observability frameworks (e.g., Monte Carlo, Databricks Lakehouse Monitoring) to proactively detect and resolve data freshness, completeness, and accuracy issues before they impact business decisions.
• Partner with the Data Governance team to ensure pipelines and data products are cataloged, lineage-tracked, and classified in Unity Catalog and/or Microsoft Purview.
• Champion metadata management and data contract enforcement as first‑class engineering practices across the platform.

• Collaborate with Data Product Managers to translate business outcomes into engineering priorities and delivery plans.
• Enable Analytics, BI, and Data Science teams with high-quality, well‑modeled data assets that…