Sr. Data Engineer

Franchise World Headquarters, LLC; Shelton (CT); On-site; USD 102,700 - 128,400; Full time

Benefits offered by this job

Insurance Plans (Medical, Life)

Pension/401K/RSP

Competitive Bonus

Tuition Reimbursement

Job summary

Franchise World Headquarters, LLC is seeking a Sr Data Engineer in Shelton, CT to lead and develop key enterprise data solutions on platforms like Databricks and Snowflake. This role requires a strong technical leader to evolve Subway's data architecture and implement high-performance frameworks.

The ideal candidate must possess 3-5 years of experience, advanced SQL skills, and the ability to work autonomously while collaborating cross-functionally. The position offers competitive compensation and benefits, making it an exciting opportunity for talented data professionals.

Qualifications

• 3–5 years of professional data engineering experience.
• Proven experience building Medallion architecture.
• Experience with CI/CD and DevOps fluency.

Responsibilities

• Design and build reference implementations on Databricks or Snowflake.
• Define enterprise data standards and patterns.
• Collaborate with various teams to translate business needs into technical directions.

Skills

Hands-on expertise in Databricks or Snowflake lakehouse platforms

Deep proficiency in PySpark

Real-time and batch streaming experience (Lambda or Kappa)

Strong data modeling skills

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Airflow

Git

AWS

Job description

We are Subway Headquarters! A dedicated team of professionals supporting thousands of franchisees around the globe.

Sr Data Engineer - Shelton, CT

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 growing franchisee profitability, strengthening the 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 is a senior‑level, hands‑on technical leader responsible for designing, building, and evolving Subway's enterprise data platform on Snowflake or Databricks. This role serves as a technical authority and builder, driving Lakehouse architecture, engineering frameworks, and best practices across multiple data domains. The Sr Data Engineer operates with a high degree of autonomy, leading through working code and influence – shipping reference implementations, POCs, and platform‑level solutions that other teams build upon.

Responsibilities

• Personally design and build reference implementations and production‑grade frameworks on Databricks or Snowflake.
• Design lakehouse platforms using Delta Lake or Iceberg Tables with Medallion (Bronze/Silver/Gold) architecture.
• Define and evolve enterprise data standards, patterns, and reusable accelerators.
• Ensure solutions align with data governance, security, scalability, and cost‑efficiency standards.
• Evaluate technologies through hands‑on benchmarking – not vendor decks.
• Build the first working version of complex pipelines, frameworks, and POCs (ingestion, CDC, streaming, DQ, observability, CI/CD).
• Drive emerging tech (Iceberg, Lakeflow, Openflow, Cortex, Mosaic AI) from POC to production rollout.
• Solve high‑complexity performance, cost, and governance challenges at petabyte scale.
• Identify and address systemic technical debt and architectural risks.
• Implement Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
• Build GenAI and ML enablement patterns (RAG, feature stores, semantic layers) using Databricks Mosaic AI or Snowflake Cortex.
• Partner with Data Science and Analytics teams to operationalize models and AI workflows.
• Collaborate closely with Product, Architecture, Security, Infrastructure, and Analytics leaders.
• Translate business needs into sound technical direction backed by working prototypes.
• Communicate technical trade‑offs, risks, and decisions clearly to technical and non‑technical stakeholders.
• Influence roadmaps and platform investments through technical insight and de‑risking POCs.
• Mentor Senior and Staff Data Engineers through pair‑programming, PR reviews, and design coaching.
• Raise engineering maturity by shipping working examples and codifying patterns.
• Foster a culture of technical excellence, learning, and continuous improvement.

Qualifications (some examples listed below)

• Exceptional hands‑on expertise in Databricks or Snowflake lakehouse platforms.
• Deep proficiency in PySpark or advanced SQL, plus Python for data engineering and automation.
• Proven experience building Medallion architecture with Delta Lake or Iceberg Tables.
• Real‑time and batch streaming experience (Lambda or Kappa) using Databricks DLT or Snowflake Dynamic Tables / Snowpipe Streaming.
• Hands‑on with orchestration tools – Airflow, Databricks Lakeflow, or Snowflake Openflow; dbt experience a plus.
• Strong data modeling skills (Dimensional, Data Vault, schema design).
• Performance and cost tuning expertise (clustering, partitioning, Z‑ordering, warehouse/cluster sizing, FinOps).
• Governance experience with Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, and data quality.
• Semantic layer experience using Databricks AI/BI Genie / Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst.
• AI/ML enablement experience with Databricks Mosaic AI or Snowflake Cortex.
• CI/CD and DevOps fluency – Git, Databricks Asset Bundles or Snowflake CLI / Schemachange, automated testing.
• Cloud ecosystem expertise – AWS (S3, Glue, Kinesis), Azure, or GCP.
• Excellent communication and technical storytelling ability.
• Comfortable operating across ambiguity and complex stakeholder environments.
• Education: Bachelor's degree required (Computer Science, Engineering, or related field); advanced degree preferred.
• Experience: 3–5 years of professional data engineering experience, with proven track record leading architecture and hands‑on build for enterprise‑scale data platforms, operating in complex or mission‑critical data environments, and influencing multiple teams and platforms without direct authority.
• Travel Requirements: Minimal to moderate (up to 10%, as business needs require).

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

Compensation: The base pay range for this role is $102,700 - $128,400 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.

EEO Statement

The Company is only considering applicants who are currently authorized to work in the country the position is based. AA/EOE/D/V