Data Engineer, Finance (R6329)

Shield AI is seeking a Data Engineer to build a reliable, governed data foundation for Finance planning and decision support. The role owns reusable integrations, semantic-layer infrastructure, and production data services on Databricks for analytics and AI-enabled applications.

Responsibilities

Build and operate scalable pipelines and integrations connecting enterprise data to Finance products

Develop semantic-layer infrastructure and governed data access for analytics, planning, and AI applications

Establish end-to-end pipeline observability, data-quality controls, and resilient operations

Engineer the services and integrations behind Databricks Genie and other AI-enabled Finance workflows

Use AI coding assistants to accelerate development while validating correctness, security, and performance

Apply FinOps practices to manage platform spend and optimize cost without compromising service quality

Partner with analytics engineers and enterprise teams on architecture, data contracts, and sustainable ownership

Preferred

Experience with Databricks, Delta Lake, cloud infrastructure, and deployment automation

Experience developing AI application backends, model integrations, or LLM-based workflows

Experience with FinOps, financial data, or enterprise-system integrations

Delta Lake

Cloud Infrastructure

Deployment Automation

AI Backend Development

Model Integration

LLM Workflows

FinOps

Financial Data

Enterprise-System Integration

Benefits

Full-time regular employee offer package: Bonus

Full-time regular employee offer package: Benefits

Full-time regular employee offer package: Equity

Temporary employee offer package: temporary benefits package (applicable after 60 days of employment)

Company

Defense-tech building AI pilots and next-generation aircraft

San Diego, California, USA

http://www.shield.ai/

Founded in 2015

1001-5000 employees

Qualifications

Hands-on 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 independent validation of generated work

Practical experience enabling AI capabilities on enterprise data, ideally in Databricks; adjacent Snowflake Cortex or comparable experience is welcome

Strong cross-functional collaboration and production ownership

Experience with Databricks, Delta Lake, cloud infrastructure, and deployment automation

Experience developing AI application backends, model integrations, or LLM-based workflows

Experience with FinOps, financial data, or enterprise-system integrations

Required skills

Represents the skills you have, click on the tags, SQL, PySpark, Databricks, Delta Lake, Snowflake Cortex, Data Modeling, AI Application Development, LLM Workflows, FinOps, Financial Data

Experience

Mid level