The Sr Data Engineer is a senior technical leader accountable for designing, building, and evolving Subway's enterprise data platform on Snowflake or Databricks. The role delivers reference implementations, proofs of concept, and platform-level solutions across multiple data domains.
Responsibilities
- Design and implement reference architectures and production-grade frameworks on Databricks or Snowflake.
- Architect lakehouse platforms using Delta Lake or Iceberg with a Medallion (Bronze/Silver/Gold) pattern.
- Define and evolve enterprise data standards, patterns, and reusable accelerators.
- Ensure solutions align with data governance, security, scalability, and cost-efficiency standards.
- Conduct hands-on technology benchmarking to evaluate options beyond vendor presentations.
- Develop the first working versions of complex pipelines, frameworks, and POCs for ingestion, CDC, streaming, data quality, observability, and CI/CD.
- Drive emerging technologies from POC to production, including Iceberg, Lakeflow, Openflow, Cortex, and Mosaic AI.
- Address high-complexity performance, cost, and governance challenges at petabyte scale.
- Identify and remediate 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 trade-offs, risks, and decisions clearly to technical and non-technical stakeholders.
- Influence roadmaps and platform investments through technical insight and de-risked 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.
Requirements
- Location: Shelton, CT onsite
- Minimum 3 years of professional data engineering experience
- Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degree preferred
- Exceptional hands-on expertise with Databricks or Snowflake lakehouse platforms
- Proficiency in PySpark or advanced SQL, plus Python for data engineering and automation
- Experience building Medallion architectures with Delta Lake or Iceberg
- Real-time and batch streaming experience (Lambda or Kappa) with Databricks DLT or Snowflake Dynamic Tables / Snowpipe Streaming
- Hands-on with orchestration tools such as Airflow, Databricks Lakeflow, or Snowflake Openflow; dbt experience is a plus
- Strong data modeling skills (Dimensional, Data Vault, schema design)
- Performance and cost tuning expertise (clustering, partitioning, Z-ordering, warehouse 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 abilities
- Comfortable operating amid ambiguity and in complex stakeholder environments
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 serves as a senior technical authority and builder, responsible for shaping Subway's enterprise data platform on Snowflake or Databricks. This role drives lakehouse architecture, engineering frameworks, and best practices across multiple data domains, operating with a high degree of autonomy and delivering reference implementations, POCs, and platform-level capabilities.
What We Offer
- Insurance Plans (Medical, Life)
- Pension or 401K/RSP depending on country
- Competitive bonus program
- Mobility allowance
- Tuition reimbursement
- Company holidays
- Volunteer time off
- Additional benefits as applicable
Compensation
The base pay range for this role is USD 102,700 to 128,400 annually. Compensation within this range will be determined in good faith based on the candidate’s skills, experience, education, and internal equity.
