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

Requirements

• Healthcare industry experience — including hands-on knowledge of Encounters data.

• Experience working with claims, member, or provider data in a healthcare payer (health insurer) or provider setting.

• 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.

• 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