Data Engineer Finance

You will build and operate data pipelines and integrations for Finance products. You will develop governed semantic-layer infrastructure, establish data-quality and observability controls, engineer AI-enabled workflow integrations, optimize platform costs, and partner on data architecture and contracts.

Responsibilities

• Build and operate scalable pipelines and integrations connecting enterprise data to Finance products.
• Develop semantic-layer infrastructure and governed data access.
• Establish pipeline observability, data-quality controls, and resilient operations.
• Engineer services and integrations for Databricks Genie and AI-enabled Finance workflows.
• Use AI coding assistants while validating correctness, security, and performance.
• Apply FinOps practices to manage platform spend and optimize cost.
• Partner on architecture, data contracts, and sustainable ownership.

Requirements

• Production data engineering experience with SQL and Python or PySpark.
• Experience with cloud data platforms, orchestration, data modeling, and governed serving patterns.
• Ability to design for observability, recoverability, security, and maintainability.
• Proficiency with AI coding assistants and validation of generated work.
• Experience enabling AI capabilities on enterprise data.
• Cross-functional collaboration and production ownership.

Benefits

• Bonus
• Benefits
• Equity