Senior Data Engineer

About the role

We are a healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions.

As a leader in SaaS technology for healthcare, we offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem. With our expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace.

Position Summary

The Senior Data Engineer owns the data platform end to end — designing, building, and maintaining the infrastructure, pipelines, and governed data layers that power analytics and downstream consumers across the organization. This is a hands-on engineering role centered on cloud data platform development, pipeline orchestration, and data modeling at scale.

The guiding principle is to build once, consume everywhere — define transformations and metrics a single time, governed and version-controlled in the warehouse, then serve them consistently to every downstream consumer: BI tools, client-facing reporting, and AI systems.

The ideal candidate is comfortable building data platforms and systems from scratch, thrive in a platform development and maintenance environment, and brings strong hands-on experience with Snowflake and workflow orchestration tools such as Apache Airflow and dbt (or equivalent platforms). This role does not own BI visualization — your work spans raw ingestion through the governed gold layer.

Key Responsibilities

Data Platform Development & Maintenance

- Design, build, and maintain scalable data pipelines and platform infrastructure on Snowflake.

- Architect and implement end-to-end data flows from source ingestion through the silver and gold layers.

- Own platform reliability, performance tuning, and ongoing maintenance — treating the data platform as a product.

- Build systems from the ground up where needed; evaluate existing systems and refactor for scale, cost efficiency, and maintainability.

- Establish engineering standards: version control, CI/CD, testing frameworks, and documentation for all platform components.

Pipeline Orchestration & Workflow Management

- Design and maintain orchestration workflows using Apache Airflow (or equivalent) to schedule, monitor, and manage data pipelines.

- Ensure pipeline reliability, observability, and failure recovery through alerting, logging, and automated retries.

- Coordinate dependencies across upstream sources and downstream consumers with well-defined SLAs.

Gold-Layer Modeling & Metrics

- Design, build, and maintain gold-layer data models and a governed metrics layer in Snowflake using dbt — clean, tested, documented, and version-controlled.