Senior Data & Analytics Engineer, Domain Enablement

Responsibilities

• Build and maintain Silver and Gold data models, domain marts, curated datasets, and semantic assets for priority domains onboarding to Databricks.
• Partner 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.
• Create reusable domain patterns and analytical building blocks for self-service analytics across FP&A, RevOps, Marketing, and other business teams.
• Support semantic views and curated layers consumed by BI tools, Databricks SQL, and Genie or related AI/BI experiences.
• Work across domain boundaries where metrics overlap, particularly across G&A, GTM, workforce, and product-adjacent concepts.
• Reflect data sensitivity, classification, and approved use in modeling choices, joins, and semantic exposure.
• Review and refine partner-delivered or domain-contributed data models for production readiness, clarity, and alignment with enterprise definitions.
• Provide patterns, documentation, examples, and technical guidance to help domain teams develop self-service analytics capabilities.

Required Qualifications

• 5+ years of experience in analytics engineering, BI engineering, data engineering, or a hybrid modeling and transformation role.
• 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.
• Data engineering fluency across Silver-to-Gold transformations, testing, performance tuning, and production deployment.
• Ability to understand business meaning and data usage constraints, not only technical transformations.
• Strong communication skills and comfort working directly with business stakeholders.

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 using SQL, PySpark, Delta Live Tables, or equivalent technologies.
• 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 G&A/GTM domains into technical domains such as Product or Engineering.