Director, Data Engineering

The Subway HR Team•Shelton, CT

3d•$184,500 - $230,600•Onsite

About The Position

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.

Requirements

8–12 years of experience in data engineering or adjacent platform roles
3–5 years of experience leading teams or enterprise-scale data capabilities
Bachelor’s degree required (Computer Science, Engineering, Data, or related field); advanced degree preferred
Deep understanding of modern data architectures (cloud data platforms, batch/stream processing)
Strong experience leading data engineering teams and platforms in a technology organization
Ability to influence across Product, Analytics, Platform, and Security; proven people leadership and delivery management skills
Experience operating cloud-based, distributed data platforms in complex, matrixed enterprise environments
Strong communication skills, executive presence, and a bias for ownership, reliability, and continuous improvement

Responsibilities

Own the data engineering roadmap aligned to data product and business priorities
Lead the design and build of scalable data pipelines (batch and streaming) and platform services
Ensure data ingestion, transformation, and delivery are reliable, observable, and performant
Drive modernization of data platforms and reduction of technical debt
Partner with Enterprise Architecture and Platform teams to align tooling, patterns, and standards; promote reusable frameworks across teams
Establish standards for data quality, observability, lineage, and documentation
Partner with Security, Privacy, and Compliance teams to ensure data protection and regulatory alignment
Collaborate with Data Product Managers to translate business outcomes into engineering priorities
Enable Analytics, BI, and Data Science teams with high-quality, well-modeled data
Lead and develop managers, leads, and senior data engineers; build strong engineering capability through hiring, coaching, and career development
Define and track KPIs (pipeline reliability, data freshness, SLAs, cost efficiency) and drive operational excellence across data platforms