Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
Partner with business and tech leadership to define requirements for high-value opportunities, deploying specialized experts to key accounts.
Lead technical hiring for Forward Deployed Engineer (FDE), evaluating data engineering expertise, systems engineering, and coding skills to build an exceptional engineering team.
Identify skill gaps in emerging tech (e.g., Model Context Protocol (MCP), tool-calling, and foundation models, building agents), ensuring the team maintains subject matter expertise in an evolving data stack.
Collaborate with product and engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.
Minimum qualifications
Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience in cloud computing, technical business engineering, or software engineering with cloud-native architectures.
2 years of experience managing a software engineering, FDE, or a related technical customer-facing team in a cloud computing environment.
Experience reviewing designs and code in Python, PySpark and SQL.
Experience designing platforms built on Data Cloud services (e.g. BigQuery, Managed Spark/Lightning Engine, Apache Iceberg (e.g., Borderless Lakehouse), Spanner, AlloyDB, Pub/Sub, Dataflow, Kafka).
Experience building agentic AI systems on enterprise data (e.g., agents, retrieval, vector search, evaluation).
Preferred qualifications
Experience leading forward deployed engineering, field engineering or professional services organizations at a data platform or AI-first company or a hyperscaler’s data and machine learning services team.
Experience engaging credibly with multi-level executives and with engineers.
Experience across a broad range of data cloud specializations, including data engineering, data science/machine learning, application development, operations, and investigative databases/data management.
Experience building end-to-end data pipelines, engineering features, and training/deploying machine learning models.
Experience with RAG architectures, chunking/indexing strategies, vector databases, hybrid search, and the use of data governance for grounding agents in enterprise context.
Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience in cloud computing, technical business engineering, or software engineering with cloud-native architectures.
2 years of experience managing a software engineering, FDE, or a related technical customer-facing team in a cloud computing environment.
Experience reviewing designs and code in Python, PySpark and SQL.
Experience designing platforms built on Data Cloud services (e.g. BigQuery, Managed Spark/Lightning Engine, Apache Iceberg (e.g., Borderless Lakehouse), Spanner, AlloyDB, Pub/Sub, Dataflow, Kafka).
Experience building agentic AI systems on enterprise data (e.g., agents, retrieval, vector search, evaluation).
