Senior Analytics Engineer - Finance (R6185)

Job Description

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 Follow Shield AI on LinkedIn, X, Instagram, and YouTube.

Job Description:

Shield AI is seeking a Senior Analytics Engineer to lead the design and delivery of trusted data products for Corporate FP&A, Accounting, Program Finance, GTM, and Strategic Finance. You will independently shape analytical solutions, establish shared standards, and turn business priorities into AI-enabled decision support on our Databricks platform. This senior individual contributor role combines hands-on engineering with cross-functional influence and mentorship to expand Finance's impact.

What you'll do:

• Shape the analytics roadmap with Finance and GTM leaders, prioritizing high-impact products and resolving competing requirements.
• Build governed datasets and semantic models that support reporting, planning, scenario analysis, and strategic decisions.
• Set modeling and metric standards across domains, exercising judgment on architecture, quality, and maintainability.
• Develop conversational analytics and AI-enabled workflows, including Databricks Genie, grounded in trusted business context.
• Use AI coding assistants to accelerate delivery and explore new capabilities while maintaining rigorous validation and quality.
• Own business-facing reconciliation and acceptance, partnering with data engineering on reliable delivery.
• Mentor engineers and Finance partners, strengthening technical practices and self-service capabilities.

Required qualifications:

• Substantial experience in analytics engineering, BI engineering, or financial data modeling, with advanced SQL and a record of delivering production data products.
• Demonstrated ability to lead ambiguous, cross-functional work from problem definition through adoption.
• Proficiency with AI coding assistants and sound judgment when reviewing generated work.
• Practical experience with AI-assisted analytics, ideally Databricks Genie; adjacent Snowflake Cortex or comparable experience is welcome.
• Sound architectural judgment, disciplined development practices, and experience mentoring others and influencing senior stakeholders.

Preferred qualifications:

• Experience with Databricks, Python, semantic layers, or AI application development.
• Experience supporting FP&A, GTM, Strategic Finance, Accounting, or Program Finance.
• Familiarity with enterprise planning, financial controls, or high-growth business environments.

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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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.