Senior Data Engineer - Snowflake & dbt Cloud

Premier Trailer Leasing•Plano, TX

About The Position

Premier Trailer Leasing is building a next-generation Enterprise Data Platform as part of a hybrid data modernization plan. This hands-on engineering role will help implement and operate a Snowflake environment, build production-grade data pipelines and models, and deliver governed data products for reporting, operational integrations, APIs, and future AI workloads. The engineer will take ownership of substantial engineering work while collaborating with Data Leadership on architecture and platform standards. Premier Trailer Leasing is one of the nation’s largest trailer leasing and rental companies, with an inventory of 70,000 trailers and a growing network of U.S. locations. The company describes its workplace as affirming and grounded in a culture of C.A.R.E.

Requirements

At least 5 years of progressive data engineering or data platform experience, including meaningful hands-on production experience with Snowflake.
Practical Snowflake experience with warehouse and workload design, RBAC, security, cost governance, performance tuning, semi-structured data, monitoring, and production operations.
Hands-on dbt Cloud experience with Git-based source control for modular transformation development, testing, lineage, documentation, environment management, CI, and production deployment.
Experience building and operating resilient ingestion, CDC, transformation, and delivery pipelines, including handling schema drift, freshness, reconciliation, failure recovery, retry, replay, and incident response.
Strong experience designing conformed enterprise models, dimensional marts, and durable data products supported by automated testing and data quality controls.
Strong proficiency in SQL, Python, Git-based development workflows, automated testing, code review, modular development, CI/CD, and controlled production releases.
Experience with practical access controls, environment separation, service-account and secrets patterns, auditability, production-change controls, and consumption monitoring.
Demonstrated hands-on ownership, clear communication of tradeoffs, ability to raise technical risks, and accountability for reliability, maintainability, documentation, and production delivery.

Nice To Haves

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.

Responsibilities

Build and operate a modern data platform using Snowflake, dbt Cloud, managed ingestion and CDC tooling, custom integrations where appropriate, and Git-based workflows.
Follow and improve practices for environments, Git workflows, modular development, testing, code review, CI/CD, deployment controls, rollback, documentation, monitoring, access, and production support.
Build layered data models covering raw ingestion, conformed enterprise models, and published marts or data products.
Develop canonical models that standardize core business entities, definitions, relationships, and rules.
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.
Profile legacy sources, inventory dependencies, identify data quality risks, reconcile existing outputs, and help migrate consumers from direct source-system access to governed data products.
Implement automated testing, reconciliation, freshness monitoring, schema-change controls, CDC-lag monitoring, alerting, failure handling, retry and replay patterns, runbooks, and production support practices.
Implement Snowflake roles, service accounts, access patterns, workload isolation, monitoring, and consumption controls to support least privilege, auditability, performance, and responsible cloud spend.
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.
Take ownership of assigned pipelines, models, integrations, and data products while collaborating with Data Leadership, the data team, and infrastructure, security, and application teams.