Lead Data Engineer

Priority Dispatch Corp.; Florida; On-site; USD 110,000 - 160,000; Full time

Job summary

El Car Wash is seeking a Lead Data Engineer to design, build, and maintain the enterprise data platform powering analytics, reporting, and business applications across the organization. You will lead scalable Snowflake-based pipelines and partner with Finance, Operations, Marketing, and Technology to deliver trusted datasets.

You will implement medallion architecture (Bronze/Silver/Gold), develop dbt models, support BI and AI initiatives, ensure data quality and governance, and advance CI/CD

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or equivalent experience.
• 5+ years in data engineering, data warehousing, or analytics engineering.
• Strong Snowflake experience with warehouse management, security, and performance optimization.
• Experience with dbt Cloud for data modeling, testing, and deployment.
• Advanced SQL with experience optimizing and modernizing legacy SQL environments.
• Experience designing dimensional data models (Kimball, SCD Type 2).
• Experience building scalable ETL/ELT pipelines using Python and orchestration tools.
• Familiarity with Azure cloud services including Azure Data Lake Storage, Data Factory, Key Vault.
• Experience with Git-based version control and CI/CD.
• Knowledge of Power BI or similar BI platforms.

Responsibilities

• Design, build, and maintain scalable data pipelines within Snowflake using Bronze/Silver/Gold architecture.
• Develop and optimize data models using dbt Cloud to create reliable datasets.
• Integrate data from multiple enterprise systems (POS, HRIS, ERP, CRM, Finance, Marketing, Operations).
• Lead migration of legacy SQL Server/Azure SQL into cloud-based architecture.
• Develop and maintain a unified enterprise data model standardizing information across sources.
• Build automated ingestion, transformation, and change-detection processes.
• Implement data quality, testing, documentation, governance best practices.
• Establish CI/CD and version control for reliable data development.
• Partner with Finance, Operations, Marketing, and Technology to deliver trusted reporting and analytics.
• Troubleshoot data issues and optimize platform performance.

Skills

Snowflake

dbt Cloud

SQL

Python

ETL/ELT pipelines

Data modeling

CI/CD

Azure

Power BI

Education

Bachelor's degree or equivalent experience

Tools

dbt Cloud

Git

Azure Data Factory

Azure Data Lake Storage

Power BI

Job description

Department: IT | Level: LeadRole Summary:The Data Engineer is responsible for designing, building, and maintaining the enterprise data platform that powers analytics, reporting, and business applications across El Car Wash. This role develops scalable data pipelines, integrates data from multiple business systems, and transforms raw data into trusted, business-ready datasets that support Finance, Operations, Marketing, Customer Experience, and Technology.As a key member of the Technology team, the Data Engineer will build and optimize our Snowflake data platform using a modern medallion architecture (Bronze, Silver, Gold), ensuring data is reliable, secure, well-governed, and accessible. This role will partner closely with cross-functional stakeholders to support business intelligence, automation, and future AI initiatives while helping standardize data across acquisitions and multiple source systems.KEY RESPONSIBILITIES:Design, build, and maintain scalable data pipelines within the Snowflake data platform using a Bronze, Silver, and Gold (medallion) architecture.Develop and optimize data models using dbt Cloud to create reliable, business-ready datasets.Integrate and manage data from multiple enterprise systems including POS, HRIS, ERP, CRM, Finance, Marketing, and operational platforms.Lead the migration of legacy SQL Server and Azure SQL data environments into a modern cloud-based architecture.Develop and maintain a unified enterprise data model that standardizes information across multiple source systems and acquisitions.Build automated ingestion, transformation, and change-detection processes to support new business applications and acquisitions.Implement data quality standards, testing, documentation, monitoring, and governance best practices.Establish CI/CD processes and version control to support reliable, scalable data development.Partner with Finance, Operations, Marketing, and Technology teams to understand business requirements and deliver trusted reporting and analytics solutions.Support business intelligence, dashboards, self-service reporting, and future AI and automation initiatives.Troubleshoot data issues, optimize platform performance, and continuously improve the reliability and scalability of the data ecosystem.QUALIFICATIONS:Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent experience.5+ years of experience in data engineering, data warehousing, or analytics engineering.Strong experience with Snowflake, including warehouse management, security, and performance optimization.Experience with dbt and dbt Cloud for data modeling, testing, documentation, and deployment.Advanced SQL skills with experience optimizing and modernizing legacy SQL environments.Experience designing dimensional data models, including Kimball methodologies and Slowly Changing Dimensions (SCD Type 2).Experience building scalable ETL/ELT pipelines using Python and modern orchestration tools.Familiarity with Azure cloud services including Azure Data Lake Storage, Azure Data Factory, Key Vault, and related services.Experience with Git-based version control and CI/CD processes.Experience integrating multiple enterprise applications and APIs.Knowledge of business intelligence platforms such as Power BI or similar visualization tools.Experience supporting retail, hospitality, automotive, or multi-location businesses is preferred.Excellent analytical, problem-solving, communication, and stakeholder management skills.Ability to thrive in a fast-paced, high-growth environment and effectively manage multiple priorities.