Senior Data Modeler
Our partner, a Fortune 500 company, is building scalable, analytics-ready data architectures for a client in the healthcare sector.
We're looking for a Senior Data Modeller to design and maintain dimensional data models using Kimball methodology that power reporting and analytics at scale. You'll translate business requirements into well-structured logical and physical models, working closely with data engineers, BI teams, and business stakeholders — with particular emphasis on healthcare Encounters data.
This is a long-term, remote-first contract position with required US working hours overlap (2-6 PM CET).
Responsibilities
Dimensional modeling: design and maintain data models using Kimball methodology (star and snowflake schemas, fact and dimension tables, SCDs).
Healthcare Encounters data: model Encounters data, ensuring accuracy and alignment with business and regulatory requirements.
Advanced SQL: develop and optimize complex queries for data extraction, transformation, and validation.
Implementation: collaborate with data engineering teams to implement models within the data warehouse/lakehouse environment.
Data quality: perform data profiling, quality checks, gap analysis, and troubleshooting across source and target systems.
Documentation: maintain data models, data dictionaries, and mapping specifications.
BI enablement: partner with BI and analytics teams to ensure models support downstream reporting needs.
Work Conditions
Type: Full-time & Long-term contract work
Start Date: ASAP
Location: Remote
US Time Zone Overlap: Required (2 PM - 6 PM CET, ideally until 7 PM CET)
Contract with EU LLC
Healthcare industry experience — including hands-on knowledge of Encounters data (must-have).
Experience working with claims, member, or provider data in a healthcare payer (health insurer) or provider setting (must-have).
Strong Kimball dimensional modeling background — star/snowflake schemas, fact and dimension tables, slowly changing dimensions (SCDs).
Advanced SQL skills — complex query writing, performance tuning, debugging, and data profiling across large datasets.
Proven ability to design logical and physical data models for data warehouses/lakehouses optimized for reporting and analytics.
Familiarity with healthcare data standards, claims processing workflows, and payer/provider data structures is a strong plus.
Excellent problem-solving skills and keen attention to detail.
Ability to collaborate with cross-functional teams and lead technical discussions with data engineers, BI teams, and business stakeholders.
Have a consultancy mindset → always try to find a solution for the client
