Data Engineer, AI & Data Platforms

We are seeking a highly skilled Senior Data Engineer with expertise in Google Cloud Platform (Google Cloud Platform) and emerging AI/Agentic technologies to build and scale next-generation data platforms. In this role, you will design and operationalize AI-enabled data solutions that support large-scale analytics, data governance, and intelligent data consumption across the enterprise.

You will partner with principal engineers, product managers, architects, and data engineering teams in a matrixed environment to deliver innovative, cloud-native data capabilities that drive business value. What You’ll Do

• Design, implement, and support modern AI-enabled data platforms on Google Cloud.
• Build scalable data ingestion, transformation, and distribution frameworks for large-scale analytics and data applications.
• Develop and operationalize cloud-native data pipelines using Spark, Kafka, Flink, and related technologies.
• Leverage AI and agentic frameworks to automate data management, governance, quality, metadata, lineage, and compliance processes.
• Create intelligent data capabilities utilizing Retrieval-Augmented Generation (RAG), GraphRAG, and agent-based architectures.
• Collaborate with cross-functional stakeholders to define technical roadmaps and deliver prioritized data solutions.
• Improve platform reliability, performance, scalability, and observability across data ecosystems.
• Support data lakehouse architecture initiatives and enterprise data modernization efforts.
• Apply engineering best practices for security, governance, and regulatory compliance.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• 5+ years of experience in Data Engineering with hands-on development and support of cloud-based data platforms.
• 5-6 years of experience working with Google Cloud Platform (Google Cloud Platform).
• Experience building and supporting data ingestion and processing pipelines using Apache Spark and PySpark.
• 3+ years of experience designing and implementing Data Lakehouse architectures.
• Proficiency in:
• Python
• PySpark
• Kafka
• Apache Airflow
• Google Cloud Storage (GCS)
• BigQuery
• Dataproc
• Cloud Composer
• Experience developing real-time and streaming data solutions using:
• Kafka
• Apache Flink
• Spark Streaming
• Recent hands-on experience with AI-enabled development frameworks and tools.

Preferred Qualifications

• 6-12 months of practical experience with modern AI and Agentic AI technologies.
• Experience building intelligent data solutions using:
• LangChain
• LangGraph
• Agent Development Kit (ADK)
• Agentic Frameworks
• Retrieval-Augmented Generation (RAG)
• GraphRAG
• Model Context Protocol (MCP)
• Knowledge of data governance, data quality, metadata management, and compliance automation.
• Strong problem-solving skills and ability to work within complex, enterprise-scale environments.
• Experience collaborating across engineering, product, and architecture teams.

Key Technologies

Cloud: Google Cloud Platform (Google Cloud Platform), BigQuery, Dataproc, Cloud Composer, Google Cloud Storage

Data Engineering: Python, PySpark, Apache Spark, Kafka, Flink, Airflow, Data Lakehouse

AI & Agentic Technologies: LangChain, LangGraph, ADK, RAG, GraphRAG, MCP, Agent-Based Architectures Must-Have Skills Summary

• 5-6 years of Google Cloud Platform (Google Cloud Platform) experience
• 5+ years of Data Engineering experience
• Data Lakehouse architecture and implementation
• Python, PySpark, Spark, Kafka, Airflow
• BigQuery, Dataproc, Cloud Composer, Cloud Storage
• Kafka, Flink, and Spark Streaming
• Hands-on exposure to AI/Agentic frameworks (LangChain, LangGraph, RAG, GraphRAG, MCP)

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