Data Engineer Sr

Overview

Built on a solid, family foundation, we've been building homes across the United States for more than 25 years, but our history started way before that in the 1600s with an English builder named George Beazer. Nine generations later, the Beazer family and name continues to stand for quality homebuilding, craftsmanship, and innovation.

Our focus is on individual communities. We strategically build each community to be near places that our customers care about, so that a home is more than a house.

Job Summary

Built on a solid, family foundation, we've been building homes across the United States for more than 25 years, but our history started way before that in the 1600s with an English builder named George Beazer. Nine generations later, the Beazer family and name continues to stand for quality homebuilding, craftsmanship, and innovation.

Our focus is on individual communities. We strategically build each community to be near places that our customers care about, so that a home is more than a house. Primary Duties & Responsibilities Build, maintain, and optimize ETL/ELT pipelines for ingesting, transforming, and processing data. Ensure data pipelines are scalable, reliable, and efficient.

Design and implement data models, warehouses, and lakehouse architectures. Optimize data storage solutions using relational (SQL) and NoSQL databases. Work with big data technologies like Spark, Hadoop, and Kafka for large-scale data processing. Deploy and manage data solutions on cloud platforms (AWS, Azure, GCP). Improve query performance and storage efficiency.

Implement indexing, partitioning, and caching strategies for faster data retrieval. Performs other duties as assigned.

Education

& Experience Typically requires a Bachelor’s degree with 8+ years experience, a Master’s degree and 6+ years experience, a PhD with 3+ years experience, or an equivalent combination of education & experience. Skills & Abilities Strong in T-SQL and Python. Expertise with ETL/ELT tools such as SSIS and Azure Data Factory.

Knowledge of both on premise and cloud database management systems. Exceled application of data modeling principles and best practices. Knowledge with Big Data concepts such as Multi Parallel Processing and Modern Cloud Data Warehouse Architecture. Excellent communication skills, both verbal and written. Exceptional analytical and problem-solving skills with keen attention to detail.

Physical Requirements This position is primarily office-based, operating in a professional and climate-controlled environment. The majority of work is performed on a computer, requiring prolonged periods of sitting, typing, and viewing a screen. The work environment is generally quiet with minimal exposure to noise, hazards, or extreme temperatures.

This position requires the ability to maintain focus and productivity in a desk-based setting, with occasional movement throughout the office for meetings or collaborative tasks. Build, maintain, and optimize ETL/ELT pipelines for ingesting, transforming, and processing data. Ensure data pipelines are scalable, reliable, and efficient.

Design and implement data models, warehouses, and lakehouse architectures. Optimize data storage solutions using relational (SQL) and NoSQL databases. Work with big data technologies like Spark, Hadoop, and Kafka for large-scale data processing. Deploy and manage data solutions on cloud platforms (AWS, Azure, GCP). Improve query performance and storage efficiency.

Implement indexing, partitioning, and caching strategies for faster data retrieval. Performs other duties as assigned. Typically requires a Bachelor’s degree with 8+ years experience, a Master’s degree and 6+ years experience, a PhD with 3+ years experience, or an equivalent combination of education & experience.