Lead Software Engineer: DevOps & Infrastructure

What you'll do

• Designs, develops, tests, and troubleshoots software and production data solutions; reviews and debugs code.
• Promotes validated, responsible AI-assisted engineering practices and automation to improve quality, delivery speed, and operational outcomes.
• Identifies recurring operational issues to automate or remediate and evaluates technical designs with vendors and internal teams.

What they ask for

• Formal training or certification in software engineering concepts.
• Hands-on experience in system design, application development, testing, and operational stability.
• Experience designing, developing, and operating ETL/ELT pipelines with Python, SQL, and distributed data-processing technologies.
• Experience with production data solutions using Databricks, Apache Spark or PySpark, Delta Lake, Lakeflow pipelines, Lakeflow Jobs, and lakehouse architecture.

Nice to have

• Experience with AI coding assistants such as GitHub Copilot and Claude Code; familiarity with prompt engineering, embeddings, or RAG pipelines.
• Experience with operational copilots or chatbots, Databricks Unity Catalog, Structured Streaming, or cloud data platforms.

Tools

Python, SQL, Databricks, Apache Spark, PySpark, Delta Lake, Lakeflow pipelines, Lakeflow Jobs

AI focus

Uses and promotes enterprise-authorized AI-assisted development for coding, testing, troubleshooting, documentation, code review, refactoring, and incident analysis; validates outputs for correctness, performance, and security, and guides peers on responsible use. Preferred work includes AI coding assistants, RAG pipelines, and operational copilots or chatbots.