Description

About the Role We are seeking a Software Engineer with expertise in modern data engineering and AI-powered platforms to help design, build, and scale next-generation data solutions on Google Cloud.

In this role, you will develop intelligent data capabilities that enable efficient data ingestion, transformation, governance, and consumption across enterprise-scale applications.

You will partner with engineers, product managers, architects, and cross-functional stakeholders to deliver scalable, secure, and automated data platforms powered by AI and agentic technologies.

Responsibilities

• Design, develop, and operationalize cloud-native data platforms and pipelines on Google Cloud.
• Build and deploy AI-enabled data capabilities to automate data management, governance, metadata management, data quality, and compliance processes.
• Implement scalable data ingestion, processing, and distribution solutions supporting large-scale analytics and business applications.
• Develop agent-based solutions using modern AI frameworks, Retrieval-Augmented Generation (RAG), GraphRAG, and Model Context Protocol (MCP).
• Create and maintain streaming and batch data pipelines using technologies such as Spark, Kafka, Flink, and Airflow.
• Partner with principal engineers, product managers, and data engineering teams to define technical roadmaps and deliver strategic data initiatives.
• Evaluate technical challenges, recommend solutions, and contribute to architectural decisions for enterprise data platforms.
• Ensure reliability, scalability, security, and operational excellence across data infrastructure and services.

Minimum Qualifications Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.

4+ years of experience in software engineering, data engineering, or related technical roles.

Experience building and supporting cloud-based data solutions.

Proficiency in Python and distributed data processing frameworks such as Spark or PySpark.

Experience designing and implementing modern data architectures, including Data Lakehouse platforms.

Experience with Google Cloud Platform (Google Cloud Platform) services including: BigQuery Google Cloud Storage (GCS) Dataproc Cloud Composer.

Experience building data pipelines using Kafka, Spark Streaming, Flink, or similar technologies.

Preferred Qualifications Hands-on experience with AI and agentic frameworks, including LangChain, LangGraph, Agent Development Kit (ADK), or similar technologies.

Experience implementing Retrieval-Augmented Generation (RAG) and GraphRAG solutions.

Experience leveraging MCP (Model Context Protocol) to build agent-based data applications.

Strong understanding of data governance, metadata management, data quality, and regulatory compliance.

Experience operating in a matrixed organization and leading cross-functional technical initiatives.

Excellent problem-solving, communication, and stakeholder management skills.

What You'll Bring A passion for building scalable, intelligent data platforms.

A strong foundation in distributed systems and cloud-native architectures.

The ability to translate complex business requirements into practical technical solutions.

A collaborative mindset and a drive to deliver high-impact outcomes in a fast-paced environment.

Industry Experience: Data Engineering, AI/ML Platforms, Cloud Engineering, Distributed Systems, Enterprise Data Architecture.

Key Skills

Education

Any Graduate