Lead Data / AI Native Engineer
Why This Role Stands Out
This hybrid role offers a fantastic opportunity to lead innovative AI-native data engineering initiatives, leveraging cutting-edge tools like GitHub Copilot and Claude Code to build scalable, cloud-native solutions on AWS and Databricks. If you're a seasoned data engineer with a passion for AI and enjoy driving complex projects, you'll thrive in this dynamic environment focused on the future of intelligent automation. Apply today to shape the next generation of AI-powered development workflows!
Quick Overview
Job Description
- Preferred Qualification
8+ years of Data Engineering and Software Engineering experience.
3+ years leading complex data engineering initiatives or engineering teams.
Proven experience building enterprise-scale data platforms and pipelines.
Experience delivering cloud-native analytics and AI solutions. Build highly available, secure, and scalable cloud-native data solutions.
Develop ETL/ELT frameworks for ingesting, transforming, and publishing enterprise data.
Implement high-volume distributed processing using Spark and PySpark.
Leverage GitHub Copilot, Claude Code CLI, and AI-assisted development tools to accelerate engineering productivity.
Technical Skills
Build Proof of Concepts (POCs) and MVPs using AI-powered development approaches.
Develop cloud-native solutions leveraging AWS and Databricks ecosystems.
Build scalable architectures for data ingestion, processing, storage, and analytics.
Key Expectations
Strong experience in building enterprise-grade data pipelines, modern Lakehouse architectures, AI-enabled data products, and cloud-native platforms leveraging Databricks, AWS EMR, Spark, PySpark, and AI-native engineering tools such as GitHub Copilot and Claude Code.
The role aligns with enterprise initiatives around AI-assisted engineering, intelligent automation, and AI-powered development workflows
Skills
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