Data Warehouse Software Engineer III

Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. We deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage. The actionable insights we deliver safeguard lives and protect critical assets around the world. Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K. For more information, visit .

We are looking for an experienced Data Warehouse Software Engineer III to own, scale, and optimize our core Google Cloud Platform (GCP) data warehousing and ingestion ecosystem!

In this role, you will be a key technical contributor responsible for architecting high-volume data ingestion pipelines into Google BigQuery, orchestrating complex workflow topologies in Apache Airflow (Cloud Composer), and maintaining the performance and reliability of our enterprise data warehouse. You will collaborate closely with cross-functional software, data, and analytics teams to integrate disparate commercial and government data sources into clean, highly available, and query-optimized data models.

This is an experienced engineering role requiring strong Python skills, deep expertise across the entire GCP analytics stack, and hands-on experience managing and upgrading production Airflow environments.

Key Responsibilities:

• Data Warehouse & Pipeline Engineering: Architect, build, and maintain production-grade ELT/ETL data pipelines that stream and batch high-volume, complex datasets into Google BigQuery.

• Airflow Management & Platform Upgrades: Manage, monitor, and upgrade our Apache Airflow / Cloud Composer platform. Write clean, modular, and maintainable DAGs in Python, implement custom operators/hooks, and optimize cluster performance.

• GCP Architecture & Optimization: Maintain and optimize core GCP data services (BigQuery, Cloud Storage, Cloud Functions/Run, Pub/Sub, IAM). Implement advanced BigQuery performance tuning (partitioning, clustering, slot management, and query cost control).

• Python Engineering & Integrations: Develop high-performance Python scripts, API connectors, and automation tools for data extraction, schema validation, and third-party data integrations.

• Data Quality & Integrity: Enforce strict data quality frameworks, monitoring, and automated alerting across all ingestion pipelines to ensure zero data loss and minimal latency.