Senior Data Engineer - Snowflake & dbt Cloud

Are you looking for a forward focus environment where you are continually challenged, and the atmosphere is affirming? Do you want to be a part of a team where you are often out of your comfort zone, but you wake up excited to go to work each day? How about a place where people are growing because they desire change and growth is modeled and expected?

WHO WE ARE:

Premier Trailer Leasing is a 'USA Today Top Workplace' and one of the largest trailer leasing and rental companies in the nation, specializing in long-term leasing and short-term rental services for over-the-road vans, flatbeds, refrigerated equipment and chassis with an inventory of 70,000 trailers and a growing network of locations across the United States. At Premier you will find an environment where you are seen, heard and valued. Join us and experience what it means to live a culture of C.A.R.E!

JOB SCOPE:

Premier Trailer Leasing is building its next-generation Enterprise Data Platform to support its continued growth as part of a hybrid data modernization plan.

This is a hands-on engineering role for an experienced data engineer with strong Snowflake experience. You will help implement and operate a Snowflake environment, build production-grade data pipelines and models, and deliver governed data products supporting reporting, operational integrations, APIs, and future AI workloads.

We are looking for someone with strong data engineering fundamentals, meaningful production experience with Snowflake and dbt Cloud, and a willingness to take ownership of substantial engineering work while collaborating with Data Leadership on architecture and platform standards.

KEY RESPONSIBILITIES:

• Platform Engineering: Build and operate a modern data platform using Snowflake, dbt Cloud, managed ingestion and CDC tooling, appropriate custom integrations, and Git-based workflows.
• Engineering Practices: Work within and help improve repeatable practices for environments, Git workflows, modular development, testing, code review, CI/CD, deployment controls, rollback, documentation, monitoring, access, and production support.
• Data Architecture & Modeling: Build layered data models spanning raw ingestion, conformed enterprise models, and published marts or data products. Develop canonical models that standardize core business entities, definitions, relationships, and rules.
• Ingestion & CDC: Build and operate resilient batch, incremental, CDC, and near-real-time ingestion patterns for SQL Server, ERP, CRM, SaaS applications, REST APIs, files, and semi-structured data using managed ingestion platforms and custom integrations where appropriate.
• Legacy Decoupling: Work with Data Leadership and the SQL Server team to profile legacy sources, inventory dependencies, identify data quality risks, reconcile existing outputs, and migrate consumers from direct source-system access to governed data products.
• Quality, Reliability & Observability: Implement automated testing, reconciliation, freshness monitoring, schema-change controls, CDC-lag monitoring, alerting, failure handling, retry and replay patterns, runbooks, and production support practices.
• Security, Cost & Performance: Implement Snowflake roles, service accounts, access patterns, workload isolation, monitoring, and consumption controls that support least privilege, auditability, performance, and responsible cloud spend.
• Data Delivery: Publish governed data products for Power BI, SSRS, Excel, HubSpot, Jira, internal and customer-facing APIs, custom applications, and a DBA-managed SQL Server serving layer for approved legacy and latency-sensitive consumers.
• Technical Ownership & Collaboration: Take ownership of assigned pipelines, models, integrations, and data products while collaborating with Data Leadership and the data team, as well as infrastructure, security, and application teams.

QUALIFICATIONS & REQUIREMENTS:

• Snowflake Experience: 5+ years of progressive data engineering or data platform experience, including meaningful hands-on production experience with Snowflake.
• Strong Snowflake Skills: Practical experience with Snowflake warehouse and workload design, RBAC, security, cost governance, performance tuning, semi-structured data, monitoring, and production operations.
• dbt Cloud Experience: Hands-on experience using dbt Cloud with Git-based source control for modular transformation development, testing, lineage, documentation, environment management, CI, and production deployment.
• Production Pipeline Ownership: Experience building and operating resilient ingestion, CDC, transformation, and delivery pipelines, including schema drift, freshness, reconciliation, failure recovery, retry, replay, and incident response.
• Data Modeling & Quality: Strong experience designing conformed enterprise models, dimensional marts, and durable data products supported by automated testing and data quality controls.
• Software Engineering Practices: Strong proficiency in SQL, Python, Git-based development workflows, automated testing, code review, modular development, CI/CD, and controlled production releases.
• Security, Governance & Cost Discipline: Experience working with practical access controls, environment separation, service-account and secrets patterns, auditability, production-change controls, and consumption monitoring.
• Ownership & Judgment: A hands-on engineer who communicates tradeoffs clearly, raises technical risks, and takes ownership of reliability, maintainability, documentation, and production delivery.

PREFERRRED EXPERIENCE:

• Experience migrating or decoupling consumers from legacy Microsoft SQL Server environments into Snowflake.
• Experience with SQL Server CDC and near-real-time ingestion.
• Experience with Kafka or other streaming/event-driven technologies.
• Experience with Dynamics GP, enterprise CRM systems, or similarly complex operational platforms.
• Experience with Azure Blob Storage, semi-structured documents, images, or other unstructured data.
• Experience with reverse ETL, operational data delivery, customer-facing data APIs, or application integrations.
• Experience with Terraform or comparable infrastructure-as-code practices.
• Experience mentoring less experienced engineers.

TECH STACK:

• Primary Platform: Snowflake
• Transformation, Testing & Lineage: dbt Cloud
• Source Control & CI/CD: GitHub, GitHub Actions, dbt Cloud CI
• Ingestion & CDC: Managed ingestion platform, SQL Server CDC, Kafka or other streaming/event-driven technologies, REST APIs, files, and custom integrations
• Primary Sources: SQL Server, Dynamics GP (ERP), CRM, SaaS applications, Azure Blob Storage, APIs, and semi-structured data
• Consumers: Power BI, SSRS, Excel, HubSpot, Jira, APIs, custom applications, SQL Server serving layers, and future AI and machine-learning workloads