Staff Data Engineer - Data Modeller

Overview

Key Responsibilities

• Data Modeling (Primary): Create, maintain, and govern conceptual, logical, and physical data models for transactional (OLTP) and analytical (OLAP/Data Warehouse) systems using ERwin Data Modeler.


• Domain Expertise: Apply deep knowledge of US healthcare standards and data structures, including HL7, FHIR, CCDA, ICD-10, and HIPAA compliance regulations.


• Physical Implementation: Define table structures, indexes, partitions, and database constraints in physical models, ensuring optimal performance for reporting and ingestion.


• Transformation: Derive physical models from logical models within ERwin, and perform reverse engineering of legacy systems to create documentation.


• Collaboration: Work with business analysts, data engineers, and architects to translate business needs into technical specifications and data mappings.


• Data Governance: Enforce data modeling standards, best practices, and naming conventions to ensure consistency and reusability across the enterprise.


• Documentation: Utilize ERwin to generate comprehensive data dictionaries, Entity-Relationship Diagrams (ERDs), and data lineage documentation.


• Tooling: Use ERwin's "Complete Compare" feature to ensure synchronization between models and live database schemas.

Required Qualifications

• Experience: 8+ years of experience in data modeling and database design.


• Healthcare Domain: Proven experience working with US Healthcare data (EMR/EHR, Claims, Member Eligibility, Provider Data).


• Tooling: Expert-level proficiency in ERwin Data Modeler (Studio).


• Modeling Techniques: Strong understanding of Normalization (3NF) and Dimensional Modeling (Star Schema/Kimball Approach).


• Technical Skills: Advanced SQL skills for data analysis, validation, and performance tuning.


• Education: Bachelor’s degree in Computer Science, Information Systems, or a related field.

Preferred Qualifications

• Experience with cloud-based data warehouses (e.g., Snowflake, AWS Redshift).


• Knowledge of Data Vault 2.0 modeling techniques.


• Familiarity with data governance tools (e.g., Collibra).

Core Competencies

• Excellent communication and interpersonal skills to explain complex technical concepts to non-technical stakeholders.


• Ability to work independently and as part of a cross-functional team.


• Strong attention to detail and ability to work in a fast-paced, regulated environment.