Analytics Engineer

We are seeking an experienced Analytics Engineer to bridge the gap between raw clinical data and regulatory reporting. The successful candidate will own the transformation of complex, version-controlled clinical data into high-performance, point-in-time KPI models that serve as the trusted source for compliance and business reporting.

Key Responsibilities

• Design and develop semantic data models by translating complex clinical and regulatory business rules into clean, modular, and high-performing SQL models.
• Build and maintain transformation logic using dbt, ensuring all calculations are version-controlled and fully reproducible through Git.
• Develop Point-in-Time (PIT) views to accurately resolve temporal relationships between transactional data and versioned dimensions.
• Deliver optimized Gold Layer star schema models that enable Business Intelligence teams to build reports without requiring complex transformation logic.
• Ensure data quality, consistency, and auditability across all transformation pipelines.
• Collaborate with data engineering, analytics, and business stakeholders to deliver scalable analytical solutions.

Technical Requirements

• Expert knowledge of dbt (Data Build Tool).
• Advanced Git version control, including branching strategies, pull requests, and release tagging.
• Expert SQL skills, including window functions, common table expressions (CTEs), complex joins, and query optimization.
• Strong understanding of dimensional modeling, star schemas, and data warehousing best practices.
• Familiarity with workflow orchestration tools such as Apache Airflow is an advantage.

Preferred Attributes

• Strong analytical and problem-solving skills.
• Experience working with healthcare or regulated datasets is desirable.
• Ability to build scalable, reusable, and maintainable data models.
• Strong attention to detail with a focus on auditability and data governance.