Job Title: Data Engineer
Location: Dublin, Ohio (Hybrid)
Must have Healthcare domain Experience
Role Overview: We are seeking a highly experienced Data Modeler to design and implement enterprise-grade data solutions. This role requires deep expertise in data modeling principles, data architecture frameworks, and modern cloud-based platforms. The candidate will play a critical role in shaping our data ecosystem, ensuring scalability, performance, and alignment with business needs.
Key Responsibilities
Data Modeling: Design conceptual, logical, and physical data models for structured and semi-structured data.
Define entity relationships, normalization/denormalization strategies, and dimensional modeling for analytics.
Develop star and snowflake schemas for data warehouses and analytical workloads.
Ensure data integrity, consistency, and compliance with governance standards.
Data Architecture: Architect end-to-end data solutions leveraging modern frameworks and best practices.
Implement Medallion architecture (Bronze, Silver, Gold layers) for scalable data pipelines.
Optimize data storage and retrieval strategies for performance and cost efficiency.
Collaborate with engineering teams to design data ingestion, transformation, and integration workflows.
Technology Stack: Hands-on experience with Google BigQuery for large-scale analytics.
Expertise in Databricks for data engineering and advanced analytics.
Familiarity with cloud-native architectures, distributed systems, and data lakehouse concepts.
Required Qualifications
· 10+ years of experience in data modeling and data architecture.
· Proven track record in designing enterprise data warehouses and analytical platforms.
· Strong understanding of Medallion architecture and modern data lakehouse design.
· Proficiency in SQL, data modeling tools (e.g., ERwin, PowerDesigner), and ETL/ELT frameworks.
· Hands-on experience with Google BigQuery and Databricks.
Skills: Preferred Skills
· Knowledge of data governance, metadata management, and master data management.
· Experience with performance tuning and query optimization in large-scale environments.
· Familiarity with data security and compliance standards.
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