Senior Data & Analytics Engineer, Domain Enablement (R5536)

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems.

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.

Responsibilities:

• 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.

Requirements:

• 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.