Data Architect

Data Architect

Franchise World Headquarters LLC

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.

Position Overview

The Data Architect is a senior technical authority responsible for defining and evolving the enterprise data platform architecture built on Databricks. This role leads the design of lakehouse streaming and batch data solutions that power analytics reporting and AI/ML use cases across the business and guides the modernization of legacy data warehouse workloads onto a modern Databricks lakehouse. The Senior Data Architect partners closely with Data Engineering Analytics Platform Security and Business teams to ensure data solutions are scalable secure cost-efficient and aligned with enterprise architecture standards while mentoring engineers on Databricks best practices.

Responsibilities

Define and lead enterprise architecture for data platforms built on Databricks including lakehouse streaming and batch architectures; architect Medallion (Bronze / Silver / Gold) pipeline patterns and design self-service capabilities leveraging Unity Catalog Delta Lake and Delta/Iceberg interoperability for domain teams.

Define architecture and migration patterns for modernizing legacy data warehouse workloads (e.g. Redshift Snowflake) onto the Databricks lakehouse; establish architecture standards design patterns and technical guardrails across the data engineering organization.

Partner with Data Engineering teams to implement robust reusable frameworks and pipeline orchestration; guide adoption of Databricks features Delta Live Tables Unity Catalog MLflow Databricks Workflows and establish monitoring observability and reliability standards for production data pipelines.

Define and enforce data governance practices data quality lineage cataloging and access controls using Unity Catalog; implement secure data access models (RBAC/ABAC) and champion metadata management and data-contract enforcement as core architecture practices.

Serve as the technical authority for data platform architecture advising Analytics BI Data Science and Product teams; lead architecture and design reviews for complex data initiatives; influence technology selection and long-term platform direction.

Mentor data engineers and architects on Databricks best practices and modern data architecture patterns; drive cost-optimization strategies for Databricks and cloud compute/storage; define and track platform KPIs reliability data freshness SLA adherence and DBU consumption efficiency.

Qualifications

Deep expertise with the Databricks platform and ecosystem Delta Lake Unity Catalog MLflow Databricks Workflows and Delta Live Tables.

Strong understanding of modern data architectures: lakehouse data lake data warehouse and data mesh concepts.

Expert-level proficiency in SQL and Python/PySpark; working knowledge of Scala is a plus.

Experience with distributed data processing frameworks (e.g. Apache Spark) at enterprise scale.

Experience with cloud platforms (AWS Azure or GCP) and native data services.

Proficiency with orchestration tools such as Databricks Workflows Airflow or Azure Data Factory.

Experience with data governance security and access-control frameworks (RBAC/ABAC).

Experience with data-quality and observability tooling (e.g. Great Expectations Monte Carlo Databricks Lakehouse Monitoring).

Working knowledge of Infrastructure-as-Code (Terraform Pulumi or ARM/Bicep).

Ability to translate business requirements into scalable cost-efficient technical designs.

Strong communication skills and ability to influence architecture decisions across engineering and business teams.

Bachelors degree in Computer Science Engineering Data Information Systems or a related field (or equivalent practical experience).

812 years of experience in data engineering data architecture or platform engineering.

Demonstrated experience architecting production-grade data platforms on Databricks Snowflake and/or Amazon Redshift.

Experience operating cloud-based distributed data platforms at enterprise scale.

Preferred Qualifications

Databricks Certified Data Engineer Professional or Databricks Certified Data/AI Solutions Architect.

Experience leading large-scale data platform migrations (e.g. Redshift to Databricks on-prem to cloud).

Exposure to ML/AI platform engineering feature stores model serving and MLOps integration.

Familiarity with Microsoft Purview Collibra or Alation for enterprise data governance.

Advanced degree (Masters) in Computer Science Engineering or a related field.

Experience in QSR Retail CPG or Franchise industry environments.

What do we offer

Insurance Plans (Medical Life)

Pension/401K/RSP (country specific)

Competitive Bonus

Mobility Allowance

Tuition Reimbursement

Company Holidays

Volunteering time

And More..

Required Experience:

Staff IC