Data Engineer

About the Role We are seeking a hands-on Senior Data Engineer to design and implement a new data warehousing environment that connects resident and medical EMR data using Snowflake. The ideal candidate is an experienced engineer who thrives in building data infrastructure from the ground up — not just a planner, but a doer who can execute. Key Responsibilities • Design, build, and implement a data warehouse in Snowflake to consolidate scattered datasets currently managed manually (including Excel-based workflows). • Establish data orchestration and workflow automation using Apache Airflow, transitioning from an existing Dagster setup. • Implement data security protocols, access control, and governance frameworks. • Work closely with stakeholders to understand business data needs and integrate data from multiple sources. • Set up and manage cloud infrastructure on AWS, ensuring scalability, performance, and reliability. • Develop and optimize ETL/ELT pipelines for data ingestion, transformation, and processing. • Collaborate with DevOps teams to automate deployments and maintain CI/CD pipelines. Required Skills & Experience • 7–8+ years of professional experience as a Data Engineer or Cloud Data Infrastructure Engineer. • Strong experience with Snowflake, Airflow, and AWS (S3, Lambda, Athena, IAM, etc.). • Proven ability to architect and implement data warehousing and data orchestration solutions from scratch. • Hands-on experience in DevOps and cloud infrastructure setup. • Expertise in data modeling, ETL/ELT pipelines, and security best practices. • Strong problem-solving, communication, and execution skills — a self-starter who can deliver with minimal supervision. Preferred Qualifications • Experience with healthcare data or EMR systems (e.g., Athena) is a plus. • Background in Python, SQL, and infrastructure-as-code tools (Terraform, CloudFormation). • Prior experience migrating from Dagster to Airflow is highly desirable.