The Senior Data & Analytics Engineer is a hybrid builder role focused on enabling business domains onto the Databricks platform by developing governed Silver and Gold assets, reusable semantic patterns, and domain-ready analytical models. This role sits between pure data engineering and pure analytics engineering: it requires enough technical depth to work comfortably with transformations and lakehouse patterns, and enough business fluency to build trustworthy models that business stakeholders can use and extend.
Initial focus for this role is expected to be G&A and GTM-oriented domains such as Accounting, Program Finance, RevOps, Marketing, HR, and adjacent business functions, while remaining flexible enough to support more complex future domains such as Product or Engineering as the team matures. This role is not a dashboard factory; it is responsible for durable, governed datasets and semantic assets that accelerate domain self-service while maintaining enterprise consistency.
What you'll do:
- Build and maintain Silver and Gold data models, domain marts, curated datasets, and semantic assets for priority domains onboarding to Databricks.
- Partner directly with business stakeholders to translate domain requirements and KPI definitions into governed, testable, and reusable transformation logic.
- Apply enterprise modeling standards, naming conventions, semantic definitions, and promotion rules, contributing practical improvements back into those standards.
- Create reusable domain patterns and analytical building blocks that allow teams such as FP&A, RevOps, and Marketing to operate more self-service over time.
- Support the design of semantic views and curated layers that can be consumed by BI tools, Databricks SQL, and Genie or related AI/BI experiences.
- Work across domain boundaries when metrics overlap or interact, especially where G&A, GTM, workforce, and product-adjacent concepts intersect.
- Ensure data sensitivity, classification, and approved use are reflected in modeling choices, joins, and semantic exposure, particularly for regulated or restricted datasets.
- Review and refine partner-delivered or domain-contributed data models to ensure they are production-worthy, understandable, and aligned with enterprise definitions.
- Help domain teams grow into more self-service analytics by providing patterns, documentation, examples, and technical guidance rather than permanently centralizing every request.
Required qualifications:
- 5+ years of experience in analytics engineering, BI engineering, data engineering, or a hybrid role spanning modeling and transformation work.
- Strong dimensional modeling and semantic design skills, including facts, dimensions, grain, conformed dimensions, and business-friendly analytical structures.
- Strong SQL skills and comfort working with modern cloud data platforms such as Databricks.
- Ability to translate ambiguous business requirements into precise, auditable, and reusable data models.
- Enough data engineering fluency to work comfortably in Silver-to-Gold transformations, testing, performance tuning, and production deployment contexts.
- Ability to understand the business meaning and usage constraints of the data being modeled, not just the technical transformations involved.
- Strong communication skills and comfort working directly with business stakeholders in domains with evolving definitions and priorities.
Preferred qualifications:
- Experience in finance, program finance, RevOps, marketing analytics, HR analytics, product analytics, or another cross-functional business domain.
- Experience building modular, tested transformation pipelines on Databricks (SQL/pyspark, Delta Live Tables, or equivalent).
- Experience with semantic layer tooling, governed metrics, or AI/BI consumption layers.
- Experience in regulated or security-sensitive industries.
- Ability and interest to expand from initial G&A/GTM domain focus into more technical domains such as Product or Engineering over time.
Skills Required
- 5+ years of experience in analytics engineering, BI engineering, data engineering, or a hybrid modeling/transformation role
- Strong dimensional modeling and semantic design skills (facts, dimensions, grain, conformed dimensions)
- Strong SQL skills and comfort working with modern cloud data platforms such as Databricks
- Ability to translate ambiguous business requirements into precise, auditable, and reusable data models
- Fluency in Silver-to-Gold transformations, testing, performance tuning, and production deployment contexts
- Ability to understand the business meaning and usage constraints of the data being modeled
- Strong communication skills and comfort working directly with business stakeholders
- Experience in finance, program finance, RevOps, marketing analytics, HR analytics, product analytics, or another cross-functional business domain
- Experience building modular, tested transformation pipelines on Databricks (SQL/pyspark, Delta Live Tables, or equivalent)
- Experience with semantic layer tooling, governed metrics, or AI/BI consumption layers
- Experience in regulated or security-sensitive industries
- Ability and interest to expand into more technical domains such as Product or Engineering
What the Team is Saying
Shield AI Compensation & Benefits Highlights
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Healthcare Strength — Healthcare coverage includes medical, dental, vision, and mental-health support, with company materials describing excellent coverage. Feedback suggests these offerings are comprehensive and consistently highlighted across official and third-party benefit lists.
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Equity Value & Accessibility — Equity is granted to all full-time hires, with RSU structures and tools like Carta Tax intended to improve understanding and tax timing. Feedback suggests this broad-based ownership approach is a notable component of total rewards.
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Parental & Family Support — Benefits include paid parental leave, fertility support, childcare benefits, family medical leave, and onsite resources such as a Mother's Room. Feedback suggests the family-oriented offerings are more expansive than basic coverage.
Shield AI Insights
What We Do
At Shield AI, you won't wait years to see your work reach the field. You'll build hardware and software that operates in the real world right now, in the hands of the people who depend on it. Hivemind, our AI pilot, has been flying since 2018. It has flown more than 30 platforms, including an F-16, and it now sits under a U.S. Air Force production contract for Collaborative Combat Aircraft. When you write code or shape a system here, you contribute to technology with a proven flight record and a clear production future. V-BAT flies intelligence, surveillance, and reconnaissance missions with an operational record that stretches from Ukraine to the Indo-Pacific. It delivers eyes where they matter most, in the most demanding conditions on earth. The teams behind it watch their work get tested where the stakes are real. X-BAT takes its first flight this year. It's an AI-piloted fighter that needs no runway, built to operate where traditional aircraft can't. Join now and you help shape a program at its earliest, most formative stage. That's the kind of ground-floor work that defines a career. Do the most impactful work of your life, on problems that matter. Autonomy at this level asks a lot of you. You'll take on problems in perception, planning, and control that few teams anywhere are equipped to solve. You'll work across disciplines, from aerospace and robotics to machine learning and systems engineering, alongside people who hold themselves to an exacting standard and expect the same from you. Our mission is clear: protect service members and civilians with intelligent systems. That purpose runs through every decision, every design review, and every deployment. It's why the work here carries a weight you can feel. Ready to join our mission? Explore our open roles and find where you fit.
Why Work With Us
Founded in 2015 by a former Navy SEAL, Shield AI builds AI pilots and uncrewed aircraft. Veterans aren't an afterthought here, they're at every level. It's why the work carries weight: AI pilots and uncrewed aircraft flying real missions, from Ukraine to the Indo-Pacific, protecting service members and civilians.
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Shield AI Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
