Staff Data Engineer

10+ years working in a data engineering role 5+ years of advanced Airflow and Python experience 3+ years of experience designing, building, and maintaining production APIs (REST, GraphQL, gRPC) 3+ years leading ML/MLOps initiatives 3+ years of hands-on experience with Google Cloud Platform (GCP) Deep expertise with columnar databases (BigQuery, Snowflake, Redshift) Demonstrated experience with AI Coding assistants Proven track record designing an end-to-end data pipeline in cloud frameworks Experience with upstream data coordination through data contracts Experience building CICD pipelines for data processing Extensive experience with infrastructure as code (Terraform, Pulumi) Expert level knowledge of data orchestration frameworks such as Apache Airflow Experience in building streaming / real-time ingestion pipelines Experience with creating alerts and monitoring pipelines Experience with containerization and container orchestration technologies Deep understanding of standard IT security practices Adaptability to learn new technologies and products Proven ability to mentor engineers and lead technical initiatives

Define and drive the technical roadmap for data infrastructure Lead the design and implementation of complex, multi-system data architectures Evaluate and champion adoption of emerging technologies in data engineering, MLOps, and GenAI Establish data governance frameworks, quality standards, and operational excellence practices Drive cross-functional initiatives Architect enterprise-scale data solutions Design and oversee the development of robust, scalable APIs Lead the evolution of event-driven and API-first data architectures Leverage Google Cloud (GCP) tools and services to architect enterprise data workloads Design resilient, self-healing data systems Lead the evolution of our data platform on Google Cloud (GCP) Define patterns for streaming and batch data architectures Establish best practices for data contracts, API versioning, CI/CD, documentation, and partner integrations Lead MLOps strategy and implementation Architect and oversee Generative AI infrastructure Partner with Data Science leadership to translate research initiatives into production-ready solutions Drive innovation in AI/ML tooling and infrastructure Mentor and guide Data Engineers at all levels Establish engineering standards, documentation practices, and knowledge-sharing processes Participate in hiring and onboarding processes Foster a culture of engineering excellence, experimentation, and continuous improvement Partner with product, engineering, and business leaders to align data strategy Communicate complex technical concepts to non-technical stakeholders Represent data engineering in cross-functional planning and architecture forums Build strong relationships with external partners and vendors