# Data Engineer, Finance (R6329)

**Company**: Shield AI
**Location**: San Diego, California
**Work arrangement**: onsite
**Experience**: senior
**Job type**: Full Time Employee
**Salary**: USD 97,000-140,000 per-year-salary
**Category**: Engineering
**Industry**: Technology

**Apply**: https://jobs.lever.co/shieldai/a3eae89e-5a2b-4e6a-8e9c-e315923b0c71?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_7ab3eeec-75d

## Description

Shield AI is seeking a Data Engineer to build the reliable, governed data foundation for Finance's next generation of planning and decision support. Working on our Databricks platform, you will own reusable integrations, semantic-layer infrastructure, and production data services that support analytics and AI-enabled applications. You will combine engineering rigor with AI-assisted development to increase delivery speed, reliability, and cost efficiency.

## 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.

## Required 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.

## Preferred Qualifications

- 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.

## Skills

### Required
- SQL
- Python
- PySpark
- Databricks
- cloud data platforms
- orchestration
- data modeling
- governed serving patterns
- AI coding assistants

### Nice to have
- Delta Lake
- cloud infrastructure
- deployment automation
- AI application backends
- model integrations
- LLM-based workflows
- FinOps
- financial data
- enterprise-system integrations

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Source: [Apply at jobs.lever.co](https://jobs.lever.co/shieldai/a3eae89e-5a2b-4e6a-8e9c-e315923b0c71?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)