Senior Analytics Engineer, Data Platform

About Virtasant Virtasant is a global technology services company with a network of over 4,000 technology professionals across 130+ countries. We specialize in cloud architecture, infrastructure, migration, and optimization, helping enterprises scale efficiently while maintaining cost control. Our clients range from Fortune 500 companies to fast-growing startups, relying on us to build high-performance infrastructure, optimize cloud environments, and enable continuous delivery at scale.

About the role We’re looking for a Senior Analytics Engineer to join us and work with our client's Data Platform team. Our client is a leading healthcare technology company, dedicated to transforming the patient and provider experience through innovative, data-driven solutions. You will bring deep expertise in data modeling, transformation design, and analytics-focused engineering. In this role, you’ll build and optimize the semantic and transformation layers that power analytics across the organization. You’ll architect dbt models, implement data quality frameworks, standardize metrics, and improve the discoverability and reliability of our client's analytics ecosystem. You’ll partner closely with data engineers, analysts, product, and platform teams to elevate how the company uses and trusts data.

What You’ll Do

Build and optimize dbt models, dimensional structures, and semantic layers. Develop high-quality SQL transformations and reusable analytics datasets. Implement data tests, validation frameworks, and lineage visibility. Collaborate with data engineers and analysts to productionize pipelines. Document models, metrics, and business logic for cross-team use.

What We’re Looking For

You have to live in the USA and have all the necessary documentation to work under an independent contractor agreement. Must-Have Experience 5+ years of experience in analytics engineering, BI engineering, or data engineering working with AWS.

3+ years of experience in healthcare, particularly demonstrated experience with processing healthcare data.

Expert SQL and production-grade dbt experience (core or Cloud) for building modular, tested, and scalable transformation pipelines.

Strong data modeling skills, including dimensional modeling, semantic layer design, and standardized metric definitions.

Hands-on experience with a major cloud data warehouse (Snowflake, BigQuery, Redshift, etc.) and understanding of performance optimization.

Familiarity with orchestration tools (Airflow, Dagster, Prefect) for scheduling and operationalizing data transformations. Solid engineering fundamentals, including Git, CI/CD pipelines, testing, and documentation in a modern software development workflow. Proven cross-functional collaboration with analysts, data engineers, and product teams to translate business needs into scalable data models. Nice-to-haves Experience building internal developer platforms or data portals Exposure to Kafka, catalogs, or lineage tools Experience with Tableau

Our recruitment process Recruiter interview (30 min) Technical Interview (45 min) Screening interview with the client's hiring manager Client technical interview A follow-up technical interview We strive to move efficiently from step to step so that the recruitment process can be as fast as possible. What we offer Totally remote within the USA, full-time (40h/week) Work hours - US Eastern time office hours