Senior Data Engineer

M3•Lawrenceville, GA

32d

About The Position

M3 (www.m3as.com) is a leading provider of hospitality-specific software solutions, delivering cloud-based tools for hotel accounting, financial reporting, labor management, payroll, and business intelligence. Built by hoteliers for hoteliers, M3 empowers hotel owners, operators, and management companies to streamline back-office operations, reduce costs, gain real-time insights, and drive portfolio performance across thousands of properties in North America and beyond. M3 is building a modern, scalable, cloud-native data platform to support analytics, governance, operational data activation, and AI-driven product capabilities. The Lead Data Engineer plays a foundational role in designing and implementing this platform on Databricks, defining architecture standards, ensuring code quality, and mentoring engineers across the data team. This is a hands-on role expected to contribute directly to implementation while elevating technical standards and guiding architectural direction. This individual is responsible for establishing architecture standards, scalable data models, pipeline engineering best practices, and CI/CD processes that enable reliable, governed, and AI-ready data across the organization. This is a hands-on senior engineering role with significant influence over long-term platform direction and technical standards.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (or equivalent practical experience).
8+ years of experience in data engineering or data platform development.
3+ years of experience designing and building cloud-based data platforms (Azure preferred; AWS or GCP acceptable; Databricks strongly preferred).
Strong expertise in SQL, data modeling, and ELT/ETL frameworks.
Experience implementing CI/CD and DevOps practices for data engineering.
Demonstrated experience building scalable, production-grade, cloud-native data systems.
Must have strong written and verbal skills in English and the ability to communicate effectively.
Must be able to build and maintain positive business relationships with co-workers and other business contacts.
This position requires regular attendance, punctuality, and the ability to work a full-time position during normal office hours as well as some time on weekends and evenings as project needs or scheduling requirements dictate.
This position requires the ability to work in an office setting, sitting at a computer workstation, with the ability to work most of the day using the computer, telephone, and basic office equipment.

Nice To Haves

Hands-on experience with data governance, metadata management, or catalog tools preferred.
Experience designing and managing data products with clear ownership, SLAs, and domain-oriented architecture principles is strongly preferred.

Responsibilities

Design, implement, and evolve M3’s cloud-native data platform architecture through direct, hands-on development.
Define and enforce standards for medallion architecture (Bronze, Silver, Gold layers).
Lead scalable data modeling efforts across financial, customer, and product domains using domain-oriented design principles and treating data assets as durable, well-defined data products.
Architect and optimize ingestion and activation pipelines (API, CDC, batch, and event-based patterns), enabling reliable bi-directional data movement between the platform and operational systems.
Implement CI/CD processes, deployment automation, and testing standards for data workflows.
Establish monitoring, observability, and performance optimization practices.
Collaborate cross-functionally with Engineering, Product, Analytics, and Business Systems teams to ensure the platform supports both analytical use cases and operational data activation back into core systems.
Define data platform architecture standards, domain boundaries, and reusable design patterns that reinforce a data-as-a-product mindset across all new development.
Establish and enforce code quality standards, conduct regular PR reviews, and implement engineering best practices across the data team.
Mentor and guide data engineers through pairing, design reviews, and structured feedback to elevate engineering quality, consistency, and architectural thinking.
Partner with external vendors when applicable and ensure knowledge transfer into internal teams.
Balance architecture leadership with active delivery, ensuring platform scalability, cost efficiency, and long-term maintainability while maintaining team velocity.