Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest, transform, and distribute data for a variety of big data apps
Leverage AI/Agentic frameworks to automate data management, governance, and data consumption capabilities including data pipelines, data quality, metadata, and data compliance
Work within a matrix organization with principal engineers, product managers, and data engineers to roadmap, plan, and deliver key data capabilities based on priority
Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering
Review and analyze complex, larger scale, or longer-term Specialty Software Engineering challenges
Requirements:
5+ years of Specialty Software Engineering experience, or equivalent demonstrated through work or consulting experience, training, military experience, or education
5+ years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
3+ years of experience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, BigQuery, Data Proc, and Cloud Composer
Demonstrable recent skills using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
Hands-on experience developing data flows using Kafka, Flink, and Spark streaming
Desired skills:
Proven experience using AI to auto-generate data engineering related code, context engineering and prompt engineering
Deep background on cloud-based data lakes and warehouses, and automated data pipelines
Public cloud certifications such as GCP Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics
Web based UI development using React and Node JS is a plus