🕒 2 days ago
Own the end-to-end data platform, designing multi-source ingestion, event-driven processing, and orchestrated workflows that deliver reliable, current data for downstream products.
Senior Data Modeler
🕒 5 days ago
Dimensional Data ModelingKimball MethodologyStar And Snowflake SchemasFact And Dimension Tables
📜 Description
- Design and maintain Kimball dimensional models, including star and snowflake schemas, fact and dimension tables, and slowly changing dimensions.
- Model healthcare Encounters data to meet business and regulatory requirements.
- Develop and optimize complex SQL queries for data extraction, transformation, and validation.
- Collaborate with data engineering teams to implement models in data warehouse or lakehouse environments.
- Perform data profiling, quality checks, gap analysis, and troubleshooting across source and target systems.
- Document data models, data dictionaries, and mapping specifications, and partner with BI teams on reporting needs.
🛠️ Requirements
- Type: Full-time & Long-term contract work
- Start Date: ASAP
- US Time Zone Overlap: Required (2 PM - 6 PM CET, ideally until 7 PM CET)
- Contract with EU LLC
Full job description
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
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