Senior Data Engineer: AI-Driven Data Pipelines and Mentorship

Namely; Los Angeles (CA); On-site; USD 158,000 - 214,000; Full time

Benefits offered by this job

Health, Dental, and Vision insurance

Flexible team structure

Opportunity for career progression

Job summary

Crexi in Playa Vista, CA, is seeking a Senior Data Engineer to design and deliver robust, scalable data pipelines, models, and infrastructure that power Crexi’s data and analytics. The role focuses on data quality, reliability, and collaboration across analytics, ML, software, and product teams.

You will mentor engineers, shape data engineering standards, and drive CI/CD improvements for data workflows while integrating AI-powered tooling to accelerate development at scale.

Qualifications

• Bachelor’s degree (or equivalent) in CS, data engineering, or a related field.
• 4+ years of data engineering experience with scalable pipelines and models.
• StrongSQL and a data engineering language (Python) with pipeline/orchestration tools.
• Experience designing scalable data models and cloud data platforms (warehouse/lakehouse).

Responsibilities

• Designs, builds, and owns scalable data pipelines and ETL/ELT workflows and underlying data models.
• Drives data quality, reliability, observability, and performance across data systems.
• Partners with analytics, ML, software, and product teams to deliver data for products and insights.
• Owns data infrastructure and orchestration and improves CI/CD for data workflows.
• Integrates AI-assisted development tools into the team’s workflow to improve quality and velocity.
• Leads resolution of complex data issues and improves system reliability.

Skills

SQL

Python

Data pipelines

Observability

Education

Bachelor’s degree in Computer Science or related field

Tools

Airflow

Cloud data platforms

Job description

Crexi in Playa Vista, CA, is seeking a Senior Data Engineer to design and deliver robust, scalable data pipelines, models, and infrastructure that power Crexi’s data and analytics. The role focuses on data quality, reliability, and collaboration across analytics, ML, software, and product teams.

You will mentor engineers, shape data engineering standards, and drive CI/CD improvements for data workflows while integrating AI-powered tooling to accelerate development at scale.