Lead Data Platform Engineer

Job Description

Job Description

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 technical leadership role for an experienced Snowflake builder. You will help design and implement a greenfield Snowflake environment, establish the engineering practices surrounding it, and deliver governed, production-grade data products supporting reporting, operational integrations, APIs, and future AI workloads.

We are looking for someone who has built and operated this kind of platform before, brings practical lessons from prior implementations, takes ownership, and constructively challenges technical assumptions. As the platform and team grow, you will establish the standards and patterns future data engineers will follow.

KEY RESPONSIBILITIES:

 

• Greenfield Platform Build: Partner with Data Leadership to design and implement a modern data platform using Snowflake, dbt Cloud, managed ingestion and CDC tooling, appropriate custom integrations, and GitHub-based workflows.
• Engineering Standards & Operating Model: Establish 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 a layered architecture spanning raw ingestion, conformed enterprise models, and published marts or data products. Design canonical models that standardize core business entities, definitions, relationships, and rules.
• Ingestion & CDC: Design and operate resilient ingestion patterns for SQL Server, ERP, CRM, SaaS applications, REST APIs, files, and semi-structured data using managed CDC and ingestion platforms alongside 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: Establish automated testing, reconciliation, freshness monitoring, schema-change controls, CDC-lag monitoring, alerting, failure handling, retry and replay patterns, runbooks, and production support expectations.
• Security, Cost & Performance: Design Snowflake environments, 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: Serve as the technical lead for the platform, owning technical quality, production readiness, design patterns, documentation, and platform stability while collaborating with Data Leadership and the data team, as well as infrastructure, security, and application teams.

QUALIFICATIONS & REQUIREMENTS:  

• Proven Greenfield Snowflake Experience: 7+ years of progressive data engineering or data platform experience, including substantial hands-on responsibility for at least one production greenfield Snowflake implementation or major platform modernization into Snowflake.
• Deep Snowflake Experience: Practical expertise with Snowflake architecture, warehouse and workload design, RBAC, security, cost governance, performance tuning, semi-structured data, monitoring, and production operations.
• dbt Cloud Expertise: Hands-on experience establishing and operating dbt Cloud with GitHub for modular transformation development, testing, lineage, documentation, environment management, CI, and production deployment.
• Production Pipeline Ownership: Experience designing and operating resilient ingestion, CDC, transformation, and delivery pipelines, including schema drift, freshness, reconciliation, failure recovery, retry, replay, and incident response.
• Data Modeling & Quality: Expertise designing conformed enterprise models, dimensional marts, and durable canonical data products supported by automated testing and data-quality controls.
• Software Engineering Practices: Strong proficiency in SQL, Python, Git and GitHub workflows, automated testing, code review, modular development, CI/CD, and controlled production releases.
• Security, Governance & Cost Discipline: Experience establishing practical access controls, environment separation, service-account and secrets patterns, auditability, production-change controls, and consumption monitoring.
• Pragmatic Technical Leadership: A hands-on builder who communicates tradeoffs clearly, challenges assumptions constructively, and takes ownership of reliability, maintainability, documentation, and production delivery.
• Location: Must be based in, or willing to commute to, the Plano, TX office at least 3 days per week.

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 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 engineers or helping establish a growing data engineering function.

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, 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