Senior Data Engineer — AI-Driven Data Platform & Pipelines

CoStar Group; Arlington (VA); Hybrid; USD 128,000 - 190,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) with matching

Paid time off

Tuition reimbursement

Commuter benefits

Stock purchase plan

On-site fitness center

Job summary

Homes.com, part of CoStar Group, seeks a Senior Data Engineer to design data architecture, build scalable pipelines, and enable data-driven insights across departments. You will shape site-wide tracking and analytics, feed KPI dashboards, and accelerate growth through robust data infrastructure and governance.

The role emphasizes collaboration with DBA, DevOps, SecOps, and product teams, with a focus on Databricks, Snowflake, and AWS, and leveraging AI tooling to improve data quality and

Qualifications

• Bachelor's degree required.
• 6+ years in software/data engineering.
• Strong proficiency in Python, PySpark, and SQL.
• Solid OO programming and design fundamentals.
• Experience building data-driven products at terabyte scale.
• Experience with cloud data platforms and BI tools.

Responsibilities

• Design dimensional models and cloud data platform structures (Databricks, Snowflake, BigQuery).
• Build secure data warehouses and data lakes using Medallion Architecture.
• Develop scalable ETL pipelines with Databricks, Snowflake, and AWS services.
• Develop and optimize Spark jobs and data transformations.
• Integrate AI/ML models into data pipelines for insights.

Skills

Python

PySpark

SQL

OO Programming

Data modeling

AI/ML understanding

Education

Bachelor's degree

Tools

Databricks

Snowflake

BigQuery

AWS

Power BI

Job description

Homes.com, part of CoStar Group, seeks a Senior Data Engineer to design data architecture, build scalable pipelines, and enable data-driven insights across departments. You will shape site-wide tracking and analytics, feed KPI dashboards, and accelerate growth through robust data infrastructure and governance.

The role emphasizes collaboration with DBA, DevOps, SecOps, and product teams, with a focus on Databricks, Snowflake, and AWS, and leveraging AI tooling to improve data quality and