Senior AI/ML Data Engineer — Real-Time Pipelines (GCP)

Public Storage; Frisco (TX); On-site; USD 130,000 - 180,000; Full time

Benefits offered by this job

In-office five days a week

Flexible remote days

Job summary

Public Storage is seeking a data engineer to advance its data platform and models, spanning batch and streaming pipelines on GCP. You will optimize data flows, ensure quality, and productionize ML workflows while collaborating with cross-functional teams in a fast-paced environment.

The role requires strong Python/SQL coding, dbt experience, and hands-on work with real-time data systems, graph data, and cloud-native tools to drive scalable analytics and decision support.

Qualifications

• 4+ years in building data pipelines (Python, SQL, dbt) in code-first environments.
• 1+ year with real-time/event-driven systems (Pub/Sub, Dataflow).
• 2+ years owning technical decisions or leading engineering direction.
• 1+ year with graph databases and graph data modeling.

Responsibilities

• Architect, build, and maintain batch and streaming data pipelines using BigQuery, dbt, Airflow, Pub/Sub, and Cloud services.
• Design scalable data models, semantic layers, and modular pipelines.
• Establish data quality, observability, lineage, and schema governance.
• Optimize BigQuery for performance and cost, including partitioning and clustering.
• Collaborate with data scientists and engineers to productionize models and data products.

Skills

Python

SQL

Data pipelines

Data modeling

Leadership

Collaboration

Education

MS in Computer Science

BS in Computer Science

Tools

BigQuery

dbt

Airflow/Cloud Composer

Pub/Sub

Dataflow

Vertex AI

Neo4j

MLflow

Evidently

Job description

Public Storage is seeking a data engineer to advance its data platform and models, spanning batch and streaming pipelines on GCP. You will optimize data flows, ensure quality, and productionize ML workflows while collaborating with cross-functional teams in a fast-paced environment.

The role requires strong Python/SQL coding, dbt experience, and hands-on work with real-time data systems, graph data, and cloud-native tools to drive scalable analytics and decision support.