Senior Developer (Data Engineer)
About the role
This isn't a traditional data engineering role focused solely on building pipelines and moving data from one system to another. This is a highly visible engineering position where you'll directly influence how business leaders make decisions across Merchandising, Supply Chain, Finance, Marketing, and Store Operations.
Responsibilities
Designing and building scalable data pipelines, data products, and integrations using Databricks, PySpark, Spark SQL, and Azure technologies
Partnering with business stakeholders to translate complex business requirements into reliable and efficient data solutions
Developing and maintaining Delta Lake tables, dimensional models, and cloud-native architectures that support enterprise analytics and reporting
Leveraging Python, SQL, Databricks, and Azure services to solve data quality, performance, and scalability challenges
Supporting Floor & Decor's strategic migration from SQL Server to Databricks by modernizing legacy workloads and improving data accessibility
Building automated monitoring, testing, and data quality frameworks that improve reliability and trust in enterprise data products
Collaborating with analytics engineers, architects, and platform teams to establish engineering standards and best practices
Leading technical initiatives, mentoring team members, and contributing to the evolution of Floor & Decor's modern data platform
Requirements
Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience preferred
5+ years of Data Engineering experience
Strong expertise in Python, SQL, Databricks, Spark, Delta Lake, and modern data engineering practices
Strong proficiency with Python and SQL
Experience working with Databricks, Spark, Azure Data Services, or similar cloud data platforms
Experience with dimensional modeling, ETL/ELT design, and enterprise data architecture concepts
Strong analytical, problem-solving, and troubleshooting skills
Proactive mindset with strong ownership, accountability, and the ability to operate independently in a fast-paced environment
Passion for continuous improvement, modern cloud technologies, and delivering high-quality engineering solutions
Qualifications
Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience preferred
5+ years of Data Engineering experience
Strong expertise in Python, SQL, Databricks, Spark, Delta Lake, and modern data engineering practices
Strong proficiency with Python and SQL
Experience working with Databricks, Spark, Azure Data Services, or similar cloud data platforms
Experience with dimensional modeling, ETL/ELT design, and enterprise data architecture concepts
Strong analytical, problem-solving, and troubleshooting skills
Proactive mindset with strong ownership, accountability, and the ability to operate independently in a fast-paced environment
Passion for continuous improvement, modern cloud technologies, and delivering high-quality engineering solutions
Skills
Python
SQL
Databricks
Spark
Azure Data Services
Dimensional Modeling
ETL/ELT Design
Enterprise Data Architecture
Benefits
See the benefits section for details.
Pay
Details about pay will be provided upon hire.
Schedule
Details about schedule will be provided upon hire.