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Sr. Data EngineerSubway • Shelton, Connecticut, United States
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Sr. Data Engineer

Subway
  • US
    Shelton, Connecticut, United States
  • US
    Shelton, Connecticut, United States
Apply Now

About

We are Subway Headquarters! A dedicated team of professionals supporting thousands of franchisees around the globe.
Senior Data Engineer
Ready to build what’s next with one of the world’s 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 what’s next.
About the Role The Sr. Data Engineer will be responsible for the design and development of data pipelines to support System Integrations as well as data pipelines that power our Analytical Platforms. In collaboration with Product Owners and other technical teams, the Sr. Data Engineer will lead significant enterprise‑wide work as part of larger cross‑functional teams supporting multiple major project initiatives. A candidate will deliver scalable, flexible, and high‑quality solutions that conform to Subway’s data design and governance strategies, leveraging our cloud data platform built on Snowflake or Databricks along with other modern cloud‑based technologies.
Responsibilities include but not limited to
Design and develop data pipelines and integrations that are performant, scalable and flexible.
Work with project teams to deliver system integration pipelines, ensuring a high degree of reliability and resiliency.
Work with business users and project teams to provide SME guidance, finalize pipeline requirements and develop level of effort estimates.
Develop automated testing and deployment scripts to support integrations and pipelines.
Provide database support by coding utilities, responding to user questions, and resolving problems.
Create and maintain documentation of data pipelines including data flow and data lineage documentation.
Responsible for tier 3 support and assisting our Operations Team as required to provide a great customer experience for our users.
Responsible for overall data quality as it relates to our Enterprise Data Warehouse and associated Data Marts. Provide data analysis as required to troubleshoot data issues.
Assist with integration related code reviews and mentorship of junior developers.
Implement data governance and master data management principles as part of data pipeline development and delivery.
Qualifications (some examples listed below)
Lakehouse Architecture: Hands‑on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog).
Medallion Architecture: Proven ability to design Bronze/Silver/Gold layers for curated, analytics‑ready data.
Streaming or Batch Processing: Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
Semantic Layer: Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst to enable consistent, governed metrics for BI and AI consumption.
ETL/ELT Orchestration: Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus.
Programming: Strong PySpark or advanced SQL skills; Python for data engineering or automation.
Data Modeling: Dimensional modeling, Data Vault, or schema design for analytical workloads.
Performance Tuning: Cluster/warehouse sizing, partitioning, clustering keys, Z‑ordering, or query optimization.
Governance & Security: Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality.
CI/CD & DevOps: Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines.
Cloud Ecosystem: AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms.
AI/ML Enablement: Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases.
Collaboration: Strong communication skills to partner with Product Owners, Analysts, or cross‑functional engineering teams.
Education: Bachelor’s degree in Computer or Information Science or related field, or equivalent combination of education and experience.
Experience: 5–8 years creating quality data pipelines and system integrations with at least 3 years of experience in a cloud environment.
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…
Compensation Base pay range for this role is $119,200 - 149,000 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.
The Company is only considering applicants who are currently authorized to work in the country the position is based. AA/EOE/D/V
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  • Shelton, Connecticut, United States

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