Senior Data Quality Engineer - Labor Management Forecasting

Publix•Lakeland, FL

3d•Hybrid

About The Position

Publix Super Markets, Inc. is seeking a Senior Data Quality Engineer to join their dynamic technology team. This role is part of the Labor Management team, responsible for designing, building, and delivering a robust application that supports Publix business areas in managing labor activities such as forecasting, time attendance, and scheduling. The engineer will own data processing validation and transformation, build and maintain scalable data pipelines, and manage Azure and on-prem data services. The position is hybrid, located in Lakeland, FL, requiring candidates to reside within a commutable distance or be willing to relocate. Publix is known for its employee-owned structure, commitment to innovation, and being a consistent "100 Best Companies to Work For" recipient.

Requirements

Bachelor’s degree in management information systems, Computer Science, Business, or other analytical disciplines or equivalent experience.
5+ years of experience in application design, development, and delivery in an enterprise environment.
5+ years of experience developing large-scale data manipulation processes.
5+ years of experience working with relational databases.
5+ years of experience implementing large scale enterprise applications.
5+ years of experience in analyzing complex, enterprise business problems or processes and translating business requirements into technology solutions that factor in system performance, usability, quality, cross-system interdependencies, scalability, and total cost of ownership.
2+ years of experience utilizing Databricks for Python.
Proficient in writing complex queries using an ANSI-compliant SQL language against an enterprise relational database management system.
Experience planning and managing all activities associated with delivering solutions in a large-scale distributed environment.
7+ years of experience in application design, development, and delivery in an enterprise environment.
7+ years of experience developing large-scale data manipulation processes.
7+ years of experience working with relational databases.
7+ years of experience implementing large scale enterprise applications.
7+ years of experience in analyzing complex, enterprise business problems or processes and translating business requirements into technology solutions that factor in system performance, usability, quality, cross-system interdependencies, scalability, and total cost of ownership.

Nice To Haves

Experience in implementing enterprise applications using platform services like azure App service, Azure SQL, Azure Service Bus, notification hubs, event hubs, Microservices, stream analytics, Snowflake DB, Redis Cache, OpenAPI, IoT Hub, application insights, etc.
Experience with Azure DevOps for managing project tasks, managing code repositories, and creating yaml pipelines for CI/CD builds and deployments.
Azure AZ-305 certification or equivalent experience in designing/architecting Azure solutions.
Experience with C# and/or Python development.
Experience with Unity Catalog, Data/Delta Lake.
Experience with advanced ML specializations (AutoML, forecasting, ensemble methods).

Responsibilities

Design and implement secure, scalable ingestion frameworks to migrate data from on prem SQL Server databases into Azure Data Lake using standardized patterns.
Develop and maintain reusable transformation frameworks (e.g., medallion architecture: bronze/silver/gold) to standardize data modeling, improve data reliability, and accelerate downstream analytics and reporting.
Establish data governance, security, and compliance controls across the lakehouse, including data classification, access controls, lineage, and auditing to ensure enterprise and regulatory standards are met.
Design, implement, and monitor data quality events to detect, alert, and resolve data anomalies across pipelines and platforms.
Provide hands-on development, deployment, maintenance, and optimization of data pipelines and workflows using Databricks.
Collaborate with technical teams and other cross-functional stakeholders to understand requirements, design solutions, and implement them using Databricks' platform.
Optimize and tune Databricks jobs for performance and scalability.
Assist technical team through problem determination and resolution on highly complex problems.
Maintain strong analytical, planning, problem solving, writing, and presentation skills.