Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, and sustain scalable data pipelines and platform infrastructure on Snowflake.

• Architect and implement comprehensive data flows from source ingestion to silver and gold layers.

• Take ownership of platform reliability, performance optimization, and continuous maintenance.

• Develop systems from inception; assess and refactor existing systems for scalability, cost-effectiveness, and maintainability.

• Set engineering standards for version control, CI/CD, testing frameworks, and documentation.

• Create and manage Apache Airflow or similar orchestration workflows to schedule, monitor, and oversee pipelines.

• Ensure pipeline reliability, observability, and recovery from failures through alerting, logging, and automated retries.

• Coordinate upstream and downstream dependencies with established SLAs.

• Design and uphold governed gold-layer data models and metrics in Snowflake using dbt.

• Establish metric definitions as a single source of truth, with clear ownership and change management.

• Move transformation and calculation logic upstream into the data warehouse.

• Collaborate with analytics and BI stakeholders on data engineering and reporting boundaries.

• Organize and document data models for AI agents and autonomous analytical systems.

• Utilize coding agents and AI-assisted tools for pipeline development, modeling, documentation, and testing.

• Set up and manage development environments, repositories, and agentic system tools.

• Assist in establishing team practices for AI-era data infrastructure.

• Advocate for data quality, consistency, and trust.

• Contribute to architectural decisions and identify opportunities for automation and process improvement.

• Assess build-versus-buy decisions and evaluate tooling trade-offs.

⛳️ Requirements

• 5+ years of practical experience in data engineering, including building pipelines, data models, and platform infrastructure in a data-centric organization.

• Proven production experience in developing data models and transformations in Snowflake, with in-depth knowledge of Snowflake architecture, performance optimization, and cost management.

• Hands-on experience with Apache Airflow or an equivalent DAG-based orchestration platform such as Prefect, Dagster, or Mage; capability to design, deploy, and manage intricate pipeline workflows.

• Demonstrated experience utilizing dbt for transformation modeling, testing, and documentation within a production warehouse environment; equivalent experience with semantic layer tooling is acceptable.

• Strong proficiency in SQL, including the ability to write, optimize, and review complex queries across substantial datasets.

• Experience in constructing data platforms or systems from the ground up.

• Comfort in platform development and maintenance as a long-term ownership model.

• Proficiency in working in the AI era, including utilizing coding agents, establishing development environments, and employing AI tools as a primary productivity enhancer.

• Familiarity with version control (Git), CI/CD pipelines, automated testing, and code review processes.

• Excellent communication skills, including the ability to translate business requirements into technical decisions for data platforms.

• Preferred experience in pharmacy benefits management, healthcare technology, or a related regulated industry.

• Prior experience with AWS, Azure, or GCP is preferred.

• Familiarity with data governance frameworks, data contracts, or data mesh principles is preferred.

• Experience with streaming or near-real-time data pipelines is preferred.

• Exposure to semantic/metrics layer tooling is preferred.

• Experience in building demo environments or client-facing data products is preferred.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and career advancement.

• Flexible work schedule and remote work options.

• Generous leave policies and paid time off.