Senior Data Modeler

Our partner, aFortune 500 company, is building scalable, analytics-ready data architectures for a client in thehealthcare sector.

We're looking for aSenior Data Modeller to design and maintaindimensional 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 onhealthcare Encounters data.

This is along-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 ofEncounters data.

• Experience working withclaims, 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 designlogical and physical data models for data warehouses/lakehouses optimized for reporting and analytics.

• Excellent problem-solving skills and keen attention to detail.

• Ability tocollaborate 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