Lead Software Engineer - Data Technology | Data Engineering

What you'll do

• Design and optimize ETL pipelines, Python applications, and distributed data processing solutions.
• Build and support AWS data services, workflow orchestration, data lake architectures, and Snowflake environments.
• Lead engineering practices and testing, and promote secure, responsible use of authorized AI-assisted development tools.

What they ask for

• Formal training or certification in software engineering concepts and 5+ years of applied experience, focused on data engineering.
• Experience developing and maintaining code in a large corporate environment, primarily with Python; Java is secondary.
• Hands-on experience with PySpark or another distributed data processing framework, strong DBT and ETL expertise, and workflow orchestration experience.
• Expertise with AWS data services, Iceberg and/or Delta Lake, Snowflake, and SQL.

Nice to have

• Experience with Kafka, Flink, or other streaming technologies; familiarity with AI/ML, LLMs, prompt engineering, vector search, and responsible AI.
• Experience with AI-assisted development tools, financial services or enterprise data environments, and mentoring engineers or leading technical delivery.

Tools

Python, Java, PySpark, DBT (Data Build Tool), Control-M, Apache Airflow (MWAA), AWS Glue, Snowflake

AI focus

Promotes enterprise-authorized AI-assisted engineering for code review and refactoring, test strategy, incident analysis, and automation, with secure coding, peer review, and automated validation. Familiarity with LLMs, prompt engineering, vector search, and responsible AI is preferred.