Senior Snowflake Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Snowflake Engineer based in the United States.

Join a data management and analytics team delivering modern data solutions for clients across a range of industries. As a Senior Snowflake Engineer, you will play a key role in building, optimizing, and maintaining robust data transformations and warehouse models using Snowflake. You will work across staging, curated, and conformed data layers, translating approved data models and business requirements into reliable, production-ready solutions. The role focuses on complex data engineering challenges, including member identity matching, historical tracking, payer attribution, and data reconciliation. You will also strengthen data quality, auditability, and operational reliability through automated checks, monitoring, and effective error handling. Working in a collaborative, client-focused environment, you will contribute technical expertise, documentation, and practical solutions that support accurate and trusted data.

• Build, develop, and optimize Snowflake SQL transformations across staging, curated, and conformed data layers.

• Implement tables, views, and transformation logic based on approved data models and source-to-target mappings.

• Develop restartable, testable, and maintainable data processing workflows with robust auditability and error handling.

• Implement patient and member identity matching logic, crosswalks, and exception handling for duplicate, unmatched, or conflicting records.

• Build and maintain dimensional models, including facts, dimensions, surrogate keys, and Slowly Changing Dimension Type 2 (SCD Type 2) history.

• Develop member-month outputs and current-state data models.

• Implement payer attribution across payers, plans, provider networks, primary care providers, and clinics while preserving monthly history.

• Reconcile modeled attribution against source rosters, documenting discrepancies and unassigned members.

• Automate data-quality checks covering row counts, null values, data types, referential integrity, and schema drift.

• Build audit, balance, and control logging, along with metrics, alerting, and reconciliation evidence.

• Troubleshoot production issues, investigate defects, and optimize query performance and processing reliability.

• Maintain technical documentation and participate in code reviews, project planning, and client demonstrations.

Requirements:

• 7+ years of experience in data engineering, data warehousing, or analytics engineering, with recent hands-on Snowflake delivery experience.

• Advanced proficiency in Snowflake SQL, including layered transformations, query optimization, performance tuning, and production troubleshooting.

• Strong experience implementing dimensional data models, including fact and dimension tables, surrogate keys, and SCD Type 2.

• Experience developing source-to-target mappings, translating complex business rules, and implementing incremental processing and reconciliation.

• Hands-on knowledge of data-quality validation, audit and control logging, error handling, and production support.

• Experience with Git-based version control, software testing, and deployment practices.

• Ability to build reliable, restartable, and supportable data pipelines with clear monitoring and audit trails.

• Strong analytical and troubleshooting skills, with the ability to investigate complex data discrepancies and resolve issues effectively.

• Healthcare payer or provider data experience is preferred.

• Familiarity with Master Patient Index (MPI), member identity resolution, or patient/member matching is an advantage.

• Strong communication and collaboration skills, including the ability to document technical solutions, contribute to reviews and planning, and participate in client-facing demonstrations.

Benefits:

• Remote working arrangement within the United States.

• Three-month contract duration.

• Full-time schedule.

• Opportunity to contribute to data management and analytics projects across diverse client environments.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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