Data Engineer, Finance

Shield; San Diego (CA); On-site; USD 97,000 - 140,000; Full time

Benefits offered by this job

Bonus

Equity

60-day benefits

Job summary

Shield AI in San Diego, CA is seeking a Data Engineer, Finance to build a reliable data foundation for Finance planning, analytics and AI-enabled workflows. You will create Databricks integrations and govern data access while ensuring production-grade reliability.

You’ll design for observability and recoverability, implement data-quality controls, and collaborate with analytics engineers and enterprise teams on data contracts and ownership, while optimizing FinOps and cost without sacrificing

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 systems with observability, recoverability, security, and maintainability.
• Proficiency with AI coding assistants and validation of generated work.
• Experience enabling AI capabilities on enterprise data, ideally in Databricks; adjacent familiarity with Snowflake Cortex or similar.
• Strong cross-functional collaboration and production ownership.

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.
• Implement end-to-end pipeline observability, data-quality controls, and resilient operations.
• Engineer services and integrations that support 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 without compromising service quality.
• Partner with analytics engineers and enterprise teams on architecture, data contracts, and ownership.

Skills

SQL

Python/PySpark

Observability

Security

Maintainability

Tools

Databricks

Snowflake Cortex

Databricks Genie

Delta Lake

Job description

Shield AI is seeking a Data Engineer, Finance in San Diego, CA (onsite) to build a reliable, governed data foundation that supports Finance planning, decision support, analytics, and AI-enabled Finance workflows. You will help create reusable Databricks integrations, strengthen semantic-layer infrastructure, and operate production-grade data services that keep teams moving with confidence.

This role blends production data engineering with platform-minded optimization. You will design for observability and resilient operations, implement data-quality controls, and work on the services and integrations behind Databricks Genie and other AI-enabled Finance workflows. Shield AI also supports faster delivery using AI coding assistants, with a strong expectation to validate correctness, security, and performance.

What you’ll do

• 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.
• Implement end-to-end pipeline observability, data-quality controls, and resilient operations.
• Engineer services and integrations that support Databricks Genie and other AI-enabled Finance workflows.
• Use AI coding assistants to accelerate development, while independently 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.

What you bring

• 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 systems with 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 experience with Snowflake Cortex or comparable platforms is welcome.
• Strong cross-functional collaboration and clear production ownership.

Technologies you’ll work with

• Databricks
• SQL
• Python
• PySpark
• Snowflake Cortex
• Databricks Genie
• Delta Lake

Compensation and benefits

$97,000 - $140,000 USD per year plus bonus, benefits, and equity.

• Pay within the listed range plus bonus, benefits, and equity.
• Pay within the listed range above plus a temporary benefits package (applicable after 60 days of employment).

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.