Cloud Data Engineer

• Build Ingestion Pipelines: Design, develop, and deploy robust data ingestion pipelines from various third-party APIs, webhooks, and source systems into Google Cloud
• AI-Augmented Engineering: Actively leverage advanced AI coding assistants to accelerate pipeline development, generate boilerplate API connection code, debug complex scripts, and automate repetitive tasks
• GCP Infrastructure & Orchestration: Build and manage data workflows using Cloud Composer (Airflow), and leverage Cloud Run and Dataflow for scalable, containerized data processing
• Drive Reverse ETL: Architect and maintain the data pipelines that push refined data from BigQuery back into our operational platforms (marketing tools, CRM, etc.) to drive business action
• Manage Operational Databases: Utilize Firestore and other NoSQL/relational databases to support operational data needs and microservices
• Collaborate and Learn: Partner with our data modeling specialists to ensure smooth handoffs between ingestion and transformation
• Participate in code reviews and continuously share new engineering best practices

• 3 to 5 years of hands-on experience in data engineering, with a strong focus on data integration, APIs, and pipeline architecture
• A strong desire to learn quickly and adapt to new technologies
• Strong Python programming skills with a proven track record of building custom API extractors, handling pagination, rate limiting, and working with REST/GraphQL endpoints
• Hands-on experience with Google Cloud Platform's ecosystem, specifically Cloud Composer, Dataflow, Cloud Run, and Firestore
• Proficient in writing clean, well-documented, and tested code (e.g., pytest), with strong experience using Git, Docker, and CI/CD pipelines
• Excellent written and verbal English communication skills

Experience managing Infrastructure as Code (specifically Terraform) or working with downstream data transformation tools (dbt)