Sr Data Engineer

Senior-level data engineering leader responsible for designing, building, and evolving Subway’s enterprise data platform on Snowflake or Databricks, delivering reference implementations, POCs, and platform-level solutions across multiple data domains.

Responsibilities

• Design and build reference implementations and production-grade frameworks on Databricks or Snowflake.
• Architect lakehouse platforms using Delta Lake or Iceberg with a 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 instead of vendor decks.
• Develop the first working versions of complex pipelines, frameworks, and POCs (ingestion, CDC, streaming, DQ, observability, CI/CD).
• Advance emerging technologies (Iceberg, Lakeflow, Openflow, Cortex, Mosaic AI) from POC to production rollout.
• Address high-complexity performance, cost, and governance challenges at petabyte scale.
• Identify and mitigate 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 with Product, Architecture, Security, Infrastructure, and Analytics leaders.
• Translate business needs into technical direction supported 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.
• Elevate engineering maturity by shipping working examples and codifying patterns.
• Foster a culture of technical excellence, learning, and continuous improvement.

Requirements

• Location: Shelton, CT onsite.
• Education: Bachelor's degree required (Computer Science, Engineering, or related field); advanced degree preferred.
• Experience: 3-5 years of professional data engineering experience, with a proven track record leading architecture and hands-on builds for enterprise-scale data platforms.
• 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 experience — AWS (S3, Glue, Kinesis), Azure, or GCP.
• Excellent communication and technical storytelling abilities.
• Ability to operate in ambiguous and complex stakeholder environments.
• Travel: Minimal to moderate travel up to 10% as business needs require.

Technologies

• Databricks
• Snowflake
• Delta Lake
• Iceberg
• Medallion architecture
• PySpark
• SQL
• Python
• Databricks Structured Streaming / DLT
• Snowflake Dynamic Tables
• Snowpipe Streaming
• Airflow
• Databricks Lakeflow
• Snowflake Openflow
• dbt
• Unity Catalog
• Horizon Catalog
• Databricks Mosaic AI
• Snowflake Cortex
• Git
• Databricks Asset Bundles
• Snowflake CLI
• Schemachange
• AWS
• Azure
• GCP
• S3
• Glue
• Kinesis

Benefits

• Medical insurance
• Life insurance
• Retirement plan (401K/RSP)
• Bonus
• Mobility allowance
• Tuition reimbursement
• Paid holidays
• Volunteer time off

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.

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: USD 102,700 - 128,400 per year. Pay within this range will be determined in good faith based on job-related factors, including skills, experience, education/training, location, and internal equity.