Location: Irving, TX
Salary: $81.00 USD Hourly - $87.00 USD Hourly
Description: Lead Software Engineer - AI & Cloud Data Engineering (Contingent)Locations: Irving, TX (preferred) | Charlotte, NC | Phoenix, AZ | Minneapolis, MN | San Antonio, TX | Des Moines, IA | New Jersey | California
Work Type: Contingent (Conversion Eligible)
About the RoleWe're building a modern, AI-enabled data platform that supports large-scale analytics and automation in a complex, hybrid-cloud environment. As a
Lead Software Engineer - AI & Cloud Data Engineering, you will play a critical role in designing, building, and operationalizing cloud-native data and AI solutions that support next-generation analytics and security use cases.
You will work in a fast-paced, highly collaborative environment alongside principal engineers, product managers, and data engineers to deliver scalable data pipelines and AI-driven automation capabilities. This is a visible, hands-on technical leadership role with meaningful impact across a large data ecosystem.
ResponsibilitiesIn this role, you will:
- Lead the design and implementation of cloud-native, AI-enabled data pipelines on Google Cloud to ingest, transform, and distribute large-scale data.
- Build and operate streaming and batch data processing solutions using technologies such as Kafka, Spark, and Flink.
- Apply AI and agentic frameworks (e.g., LangChain, LangGraph, RAG/GraphRAG) to automate data management, governance, quality, metadata, and compliance workflows.
- Consult on complex, large-scale data engineering initiatives, contributing to architectural decisions and long-term platform strategy.
- Collaborate strategically within a matrixed organization, partnering with engineers, product managers, and stakeholders to roadmap and deliver high-priority data capabilities.
- Drive adoption of modern data and AI technologies through technical leadership, mentorship, and hands-on development.
- Support the migration of on-premises data platforms to Google Cloud-based architectures.
- Ensure solutions align with organizational standards, security requirements, and compliance expectations.
Minimum Qualifications- 5+ years of experience in software or data engineering, or equivalent experience gained through work, consulting, education, military service, or training.
- Experience working in large-scale data environments.
- Hands-on experience building and supporting cloud data solutions, including Spark-based ingestion and processing.
- Strong proficiency in Python and experience with Kafka.
- Demonstrated experience developing data pipelines on Google Cloud, including services such as:
- Google Cloud Storage
- BigQuery
- Dataproc
- Cloud Composer (Airflow)
- Experience with data lakehouse architectures and modern data processing patterns.
- Proven ability to work on complex, ambiguous technical problems requiring in-depth analysis and sound judgment.
Preferred Qualifications- Recent, hands-on experience with AI tooling and frameworks, including:
- LangChain
- LangGraph / ADK
- Agentic frameworks
- Retrieval-Augmented Generation (RAG) and GraphRAG
- MCP-based agent architectures
- Experience using AI to accelerate data engineering, including code generation, context engineering, and prompt engineering.
- Hands-on experience with streaming technologies (Kafka, Flink, Spark Streaming).
- Strong background in cloud-based data lakes and warehouses with automated data pipelines.
- Public cloud certifications (e.g., Google Cloud Platform Professional Data Engineer, Azure Data Engineer, AWS Data Analytics Specialty).
- Experience with web-based UI development (React, Node.js) a plus.
Why This Role- Opportunity to build a modern AI-powered data platform from the ground up
- High-impact work with visibility across engineering and product teams
- Exposure to cutting-edge AI, data engineering, and cloud-native technologies
- Collaborative environment that values innovation, technical excellence, and continuous learning
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