Shelton Data Engineering Dir- Data Engineering

Ready to build whats next with one of the worlds most iconic brands

Why Join Subway

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 whats next.

About the Role:

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:

Data Platform Engineering & Architecture

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• Own the design development and operations of Subways enterprise data engineering platform on AWS Databricks including migration strategy from the existing Amazon Redshift environment.
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• Lead the delivery of Medallion Architecture (Bronze / Silver / Gold) pipelines across all QSR domains Restaurant Sales Inventory Guest Marketing and Supply Chain.
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• Oversee development of Delta Live Tables batch and streaming pipelines and feature engineering workflows across Databricks and Microsoft Fabric.
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• 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.
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• Define and execute the platform migration roadmap phasing workloads from Redshift to Databricks/Snowflake with minimal business disruption.
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• 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.
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DataOps & Platform Reliability

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

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• 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.
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• 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.
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• 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.
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• Champion metadata management and data contract enforcement as first-class engineering practices across the platform.
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Cross-Functional Partnership

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• Collaborate with Data Product Managers to translate business outcomes into engineering priorities and delivery plans.
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• Enable Analytics BI and Data Science teams with high-quality well-modeled data assets that accelerate insight generation.
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• Communicate platform health tradeoffs and delivery status to business and technology stakeholders through regular forums and reporting.
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Stakeholder Engagement & Strategic Planning

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• Serve as the primary data engineering partner to product and domain leaders translating business needs into engineered scalable data solutions.
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• Lead vendor relationships and participate in technology evaluations RFPs and contract negotiations for data platform tooling and services (Databricks Snowflake dbt Fivetran etc.).
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• Manage the data engineering budget including cloud infrastructure costs (AWS Azure) tooling licenses DBU consumption and contractor spend.
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• Develop and present quarterly technology roadmaps to senior leadership aligning platform investments to enterprise data and AI strategy.
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• Collaborate cross-functionally with Application Engineering InfoSec and Enterprise Architecture to ensure platform alignment with enterprise standards.
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Team Leadership & Talent Development

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• Lead and develop managers leads and senior data engineers across onshore and offshore delivery models.
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• Set clear goals performance expectations and delivery standards aligned to organizational OKRs.
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• Build strong engineering capability through hiring coaching and career development scaling the team to 1020 engineers (FTEs and contractors).
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• Establish engineering standards code review practices and a culture of continuous improvement and technical excellence.
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• Foster a culture of ownership reliability and continuous improvement within the data engineering function.
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Performance & Optimization

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• Define and track KPIs including pipeline reliability data freshness SLA adherence and cost efficiency.
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• Drive operational excellence automation and cost optimization across all data platforms and infrastructure.
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• Support incident analysis and preventative improvements to continuously raise the reliability bar.
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Qualifications (some examples listed below):

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• Strong experience leading data engineering teams and platforms in a technology-forward organization.
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• Deep understanding of modern data architectures cloud data platforms batch/stream processing lakehouse and data mesh.
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• Experience balancing delivery speed with governance reliability and scalability in complex environments.
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• Ability to influence across Product Analytics Platform and Security functions.
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• Proven people leadership delivery management and vendor management skills.
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• Strong communication skills and executive presence; comfortable presenting to C-suite stakeholders.
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• Expert in SQL Python and PySpark; working knowledge of Scala is a plus.
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• Proficient with orchestration tools (Databricks Workflows Airflow Azure Data Factory).
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• Experience with data quality and observability tools (Great Expectations Monte Carlo Soda or equivalent).
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• Familiarity with dbt Fivetran/Airbyte or similar ELT frameworks.
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• Working knowledge of Infrastructure-as-Code (Terraform Pulumi or ARM/Bicep).
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• Bachelors degree required (Computer Science Engineering Data Information Systems or related field).
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• Advanced degree (Masters or MBA) preferred.
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• 812 years of experience in data engineering or adjacent platform roles.
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• 35 years of experience leading teams or enterprise-scale data capabilities.
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• Demonstrated experience delivering production-grade data platforms on Databricks (strongly preferred) Snowflake and/or Amazon Redshift.
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• Experience operating cloud-based distributed data platforms at enterprise scale.
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• Experience in complex matrixed enterprise environments QSR Retail CPG or Franchise industries preferred.
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Preferred Qualifications

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• Databricks Certified Data Engineer Professional or equivalent certification.
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• Experience leading large-scale data platform migrations (e.g. Redshift to Databricks on-prem to cloud).
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• Exposure to ML/AI platform engineering feature stores model serving and MLOps integration.
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• Experience with FinOps practices for cloud cost optimization and chargeback models.
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• Familiarity with Microsoft Purview Collibra or Alation for enterprise data governance.
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What do we offer

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• Insurance Plans (Medical Life)
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• Pension/401K/RSP (country specific)
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• Competitive Bonus
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• Mobility Allowance
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• Tuition Reimbursement
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• Company Holidays
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• Volunteering time
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• And More..
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Compensation: The base pay range for this role is $184500 - 230600 annually

Pay within this range will be determined in good faith based on job-related factors which may include skills experience education/training location and internal equity.

Required Experience:

IC