About the Job
At Prenuvo, we are on a mission to flip the paradigm from reactive “sick-care” to proactive health care. Our award-winning whole body scan is fast (under 1 hour), safe (MRI has no ionizing radiation), and non-invasive (no contrast). Our unique integrated stack of optimized hardware, software, and increasingly AI, co...
We are looking for a Senior Analytics Engineer, to lead enterprise modeling and semantic architecture, raise engineering standards, and help the Data & Analytics team scale through shared patterns, mentorship, and governed data products.
This role does not provide visa sponsorship. Applicants must be legally authorized to work in the United States at the time of hire and must not require employer sponsorship for a work visa (current or future).
Key Responsibilities
Drive the implementation and continued evolution of enterprise analytical modeling standards, including domain boundaries, shared entities, dimensional design, and semantic layer architecture.
Create practical standards for model design, testing, documentation, lineage, observability, access, code review, and release management.
Guide the transition from one off marts and dashboard specific logic toward reusable, governed data products.
Collaborate closely with data team members by leading architecture reviews, guiding system design, and co-owning high-impact technical choices.
Lead cross domain design with Product, Engineering, Finance/Accounting, Clinical, Research, Growth/Marketing, and AI stakeholders.
Define how trusted measures and dimensions are exposed across Sigma, analytical workflows, and governed AI experiences.
Support data quality ownership by connecting business definitions, source system accountability, automated controls, and incident response.
Execute and operationalize the enterprise data governance framework in partnership with Data leadership, translating organizational direction into clear standards, ownership models, quality controls, documentation, and adoption practices across teams.
Required Skills & Abilities
At least 4 years of experience in analytics engineering, data engineering, data architecture, or a related discipline.
Deep expertise in SQL, dbt, dimensional modeling, data warehouse design, and reusable analytical data product development.
Hands on experience designing semantic or metrics layers used across multiple analytical consumers.
Strong knowledge of testing, observability, lineage, metadata, access controls, privacy aware architecture, and software development lifecycle practices.
Demonstrated ability to lead architecture through influence, create clear technical decision records, and mentor experienced engineers.
Experience balancing enterprise consistency with iterative delivery and domain specific needs.
Strong communication skills with the ability to connect technical choices to organizational risk, speed, cost, and business outcomes.
Experience with Databricks, Fivetran, Sigma, and dbt MetricFlow or a comparable semantic layer platform.
Experience working with healthcare data in a regulated environment, with a strong understanding of privacy, governance, and responsible data use.
Experience designing data contracts, domain oriented data products, or a data governance operating model.
Experience modernizing a growing analytical environment without disrupting critical reporting.
Qualifications
Experience:
4 years experience
