Location: Phoenix, AZ
Salary: $52.00 USD Hourly - $57.00 USD Hourly
Description: Senior Data Engineer, AI & Data Platforms (Google Cloud)We are not accepting C2C or 1099 arrangements.Location: Preferred: Chandler, AZ | Charlotte, NC | Minneapolis, MN | Irving (Las Colinas), TX
Employment Type: Contingent/Contract
About the RoleWe 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.
Minimum Qualifications- 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 TechnologiesCloud: 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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