Forward Deployed Engineer

As a Forward Deployed Engineer, you will:

• Deploy, configure, and execute data pipelines directly within client environments, performing precise field-level data mapping between customer schemas and internal platform data models.

• Lead the technical translation and migration of existing backend data pipelines, workloads, and cloud infrastructure from Microsoft Azure over to Google Cloud Platform (GCP).
• Design, build, and optimize Python-native data engineering pipelines, leveraging BigQuery as the primary high-performance datastore.
• Establish and manage cloud infrastructure and orchestration workflows using tools such as Cloud Run, Apache Airflow, or similar native GCP services.
• Configure Vertex AI for model registry and ML platforms, and utilize Spark/PySpark to optimize computationally intensive tasks such as network-graph calculations.
• Leverage AI-assisted developer tooling (e.g., GitHub Copilot) for efficient code generation, review, and overall engineering productivity.

Must-Haves

• Core Data Engineering Skills: 4+ years of hands-on proficiency in Python and extensive experience using Google BigQuery as a core input/output storage engine.
• Orchestration & Infrastructure: Experience setting up cloud infrastructure and orchestrating data workflows (Airflow, Cloud Run, or equivalent).
• Client-Facing / Forward-Deployed Mindset: Experience adapting standard engineering solutions to diverse, client-specific schemas and environment constraints.

Nice-to-Haves

• Experience porting data pipelines and infrastructure from Microsoft Azure to GCP.
• Official Google Cloud certification (e.g., Associate Cloud Engineer, Professional Data Engineer, or Professional Cloud Architect).
• Experience with Apache Spark or PySpark for complex data processing (e.g., network graph calculations).
• Hands-on experience with Vertex AI for AI platform setups and model management.
• Familiarity with AI-assisted software development tools like GitHub Copilot.