Infrastructure Software Engineer (Python · GCP · Data Pipelines)

# About the role

They are looking for an Infrastructure Software Engineer to join an engineering team that is driving a technology modernization. The work is cloud-native infrastructure on Google Cloud and moving data at scale between systems, for example streaming data from Spanner and other cloud databases into BigQuery.

This is a software engineering role first, not a traditional data engineering role. They value strong engineering fundamentals over specific data tools.

# Responsibilities

• Design, build and maintain cloud-native infrastructure on GCP using Terraform.

• Build and operate pipelines that chain GCP services (Pub/Sub, Cloud Run, Cloud Composer/Airflow, Dataflow/Apache Beam) to move data through the system.

• Write production-quality code, mainly in Python, and use Spark for distributed processing.

• Apply the full SDLC: design, code reviews, unit and functional tests, CI/CD build pipelines.

• Work with SQL-strong teammates on BigQuery queries, merges and data models.

• Use AI tools effectively to speed up delivery on complex infrastructure work.

# Requirements

• 7 years of experience as software engineer with background building production systems.

• Strong SDLC practices: writing unit and functional tests, working with build/CI pipelines.

• Python, or Java: strong Java engineers are welcome and can ramp up on Python.

• Infrastructure / DevOps experience: Infrastructure as Code (Terraform) and cloud services (GCP preferred, AWS accepted).

• Experience building or maintaining data pipelines that move data between systems.

• Spark (basic distributed compute).

• GCP services: Pub/Sub, Cloud Run, Cloud Composer/Airflow, Dataflow/Apache Beam, Spanner.

• BigQuery and SQL.

• Job scheduling and orchestration.

• Engineer-first mindset: able to design and build new infrastructure end to end, not only run queries or ETLs.

• Fast learner: picks up new tools (for example Spark) in weeks.

• Comfortable with a structured onboarding focused on SDLC and build pipelines before project work.

• Collaborative and proactive.

• English to work daily with a US-based team.