Senior Data Modeler
About The Position
We are seeking a Senior Data Modeler to lead the assessment and redesign of a legacy data ecosystem into a modern, scalable data lake architecture. This role will define the target-state data architecture and operating model across ingestion, standardization, validation, curated datasets, and governance in a complex, multi-partner environment. The engagement will culminate in a structured gap analysis and phased migration roadmap, with clear sequencing and implementation recommendations. The ideal candidate brings deep modeling expertise, architectural clarity, and the ability to stabilize downstream processing ecosystems through disciplined data design and governance.
Requirements
- Advanced expertise in logical and physical data modeling across structured and semi-structured data
- Strong experience designing canonical data models and standardization strategies
- Deep understanding of dimensional modeling, including star and snowflake schemas
- Practical knowledge of Data Vault and hybrid modeling approaches
- Experience transforming legacy data platforms into modern data lake or lakehouse ecosystems
- Proven track record addressing systemic data quality issues at scale
- Experience designing ingestion frameworks for heterogeneous data sources
- Strong grasp of metadata management, lineage, and observability concepts
- Experience defining governance models and stewardship frameworks
- Demonstrated ability to conduct structured assessments, gap analysis, and roadmap development
- Strong stakeholder engagement and architectural communication skills
Nice To Haves
- Experience leading enterprise-scale data modernization initiatives
- Demonstrated success in stabilizing downstream batch ecosystems through improved modeling and governance
- Experience delivering phased migration roadmaps in complex, multi-partner data environments
- Experience supporting healthcare payer data domains such as claims, enrollment, providers, or quality reporting
Responsibilities
- Assess existing data ingestion pipelines, storage structures, data models, and batch processing dependencies
- Identify root causes of recurring data quality issues, lineage gaps, and downstream performance bottlenecks
- Design a scalable, layered data architecture supporting raw ingestion, standardized data, and curated consumer-aligned datasets
- Define canonical data models to standardize heterogeneous partner data across formats
- Recommend and apply appropriate modeling approaches, including dimensional, Data Vault, normalized, or hybrid models
- Establish data validation, enrichment, and transformation patterns that improve reliability and consistency
- Define data quality rules, validation checkpoints, naming conventions, and metadata standards
- Design data contracts and schema evolution strategies to support partners onboarding and backward compatibility
- Establish governance and ownership models, including data stewardship and accountability frameworks
- Define metadata management, lineage tracking, observability, and lifecycle management standards
- Conduct structured gap analysis between current and target states
- Develop a phased migration roadmap that minimizes operational risk and stabilizes downstream batch ecosystems
- Provide implementation recommendations across people, process, tooling, and governance
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
