Description

Responsibilities:

• 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

Key Skills

Education

Bachelor's degree