On-Demand Group

Senior Data Modeler and Looker Architect

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Modeler and Looker Architect with 5–10+ years of healthcare data modeling experience. Contract length is 6–12 months, remote work, and requires expertise in GCP and Looker/LookML for enterprise data architecture modernization.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
680
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🗓️ - Date
December 5, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Documentation #Data Modeling #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform) #Data Design #Looker #Scala #Data Warehouse #Semantic Models #Data Engineering #Data Architecture
Role description
Title: Senior Data Modeler & Looker Architect (Healthcare) Location: Remote Duration: 6–12 Months Employment Type: Contract On-Demand Group is seeking a highly skilled Senior Data Modeler & Looker Architect with strong healthcare industry experience, deep expertise in GCP, and hands-on proficiency with Looker/LookML. This role will support a major modernization initiative, helping transform a lifted-and-shifted data warehouse into a fully designed, scalable greenfield data architecture. This is a hands-on, highly technical role focused on foundational data modeling, semantic layer development, and enterprise Looker implementation support. We are looking for someone who has “been there, done that” across healthcare data environments and can bridge business, data, and engineering teams. Responsibilities Workstream 1: Foundational Data Modeling (GCP) • Design and develop core, reusable, scalable data models for a modernized greenfield warehouse environment. • Support the transformation from a legacy lift-and-shift architecture to a properly structured lakehouse model. • Work closely with data engineering and product teams to define what needs to be built and ensure alignment with business requirements. Workstream 2: Semantic Layer Data Modeling in Looker • Build LookML semantic models from scratch to support governed, consistent, self-service analytics. • Create a semantic layer allowing product, analytics, and business teams to easily access and understand enterprise data. • Ensure high-quality standards, documentation, and maintainable modeling practices. Workstream 3: Looker Enterprise Rollout Support • Provide architectural and hands-on guidance for an enterprise-grade Looker rollout. • Support content governance, data modeling excellence, and best practices for scaling Looker across the organization. • Partner with cross-functional teams to gather requirements, align data definitions, and promote user adoption. Cross-Functional Responsibilities • Serve as the bridge between technology, product, finance, legal, and other business areas. • Translate complex business needs into actionable technical solutions. • Ensure enterprise data models, Looker structures, and reporting layers are built correctly from the start. • Support healthcare data products, analytics workloads, and commercialization initiatives. Required Skills & Experience • 5–10+ years of data modeling experience, including modern data architectures and enterprise data warehousing. • A strong healthcare industry background is required. • Advanced Looker/LookML expertise, including building semantic layers from scratch. • GCP experience required; GCP Architect or equivalent experience strongly preferred. • Proven experience supporting large-scale data platform modernization efforts. • Experience with semantic modeling, dimensional modeling, and analytics data structures. • Ability to work in a fast-paced, cross-functional, and highly collaborative environment. • Strong communication skills; able to translate between technical teams and business stakeholders. • Hands-on, solution-oriented mindset. Preferred Qualifications • Experience supporting enterprise analytics rollouts. • Background in lakehouse architectures or greenfield data design. • Prior success in modernizing data ecosystems in healthcare organizations.