Pay
Lower than most similar jobs
$97K–$140K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Data Engineer, Finance
San Diego, California
Live, first seen by us 17 days ago- Pay
USD 97,000–140,000/year — pay source
Salary 97,000 – 140,000 USD per year #LI-RS3
Read the full posting- Work setting
On-site — work setting source
Work setup in the employer’s posting: onsite
From the employer’s posting- Employment
Full-time — employment source
Employment type Full Time Employee
Employment type in the employer’s posting: Full Time Employee
From the employer’s posting
What you’ll work on
Full postingBuild and operate scalable pipelines connecting enterprise data to Finance products
Develop semantic-layer infrastructure and governed data access for analytics and AI
Establish pipeline observability, data-quality controls, and resilient operations
Engineer services and integrations behind Databricks Genie and other AI Finance workflows
Apply FinOps practices to manage platform spend without hurting service quality
From the employer’s posting
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.
Apply FinOps practices to manage platform spend and optimize cost without compromising service quality.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree in computer science or a related technical or quantitative field and a minimum of 2 years of related experience.
- 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.
Preferred experience
- 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.
Qualification wording
Bachelor’s degree in computer science or a related technical or quantitative field and a minimum of 2 years of related experience.
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.
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.
Education & alternatives
Required qualifications: - Bachelor’s degree in computer science or a related technical or quantitative field and a minimum of 2 years of related experience. - Hands-on production data engineering experience with SQL and Python or PySpark.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 18, 202617 days ago
- Recorded sightings
- 95
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 17
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
Shieldai is hiring
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is picking up
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- Databricks
- Delta Lake
- Snowflake
- PySpark
Where the posting names them
- Bachelor’s degree in computer science or a related technical or quantitative field and a minimum of 2 years of related experience. - Hands-on production data engineering experience with SQL and Python or PySpark. - Experience with cloud data platforms, orchestration, data modeling, and governed serving patterns.
Job 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. What you'll do:
- 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.
- 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.
Your next step
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About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job 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.
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.
- 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:
- Bachelor’s degree in computer science or a related technical or quantitative field and a minimum of 2 years of related experience.
- 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.
Salary
97,000 – 140,000 USD per year
#LI-RS3
#LB
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
Employment type
Full Time Employee
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 97,000 – 140,000 USD per year #LI-RS3
- Location & working pattern
San Diego, California
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.