Senior Data Engineer

MDCalc is a leading medical reference used by over 65% of physicians worldwide, focusing on improving patient outcomes through evidence-based tools. They are seeking a Senior Data Engineer to design and maintain data infrastructure, ensuring reliable analytics and product insights while collaborating closely with product and business teams.

Responsibilities:

• Design, build, and maintain scalable data pipelines and ELT/ETL workflows that support analytics, operational reporting, and business intelligence use cases
• Build programmatic data pipelines (primarily in Python) that extract data from application and third-party systems, transform it into usable formats, and deliver it to downstream data platforms and consumers
• Own and improve core data models and transformations to ensure data is accurate, well-structured, and easy for stakeholders to use
• Partner with Product, Engineering, and Analytics teams to understand data needs and translate them into reliable data solutions
• Develop and maintain systems that move data across the platform, ensuring it is properly shaped, structured, and available for downstream analysis and product use cases
• Help shape and maintain the architecture of MDCalc’s modern data stack, including warehousing, orchestration, transformation, and monitoring
• Improve data quality, observability, and reliability through testing, validation, and proactive monitoring practices
• Support the ingestion and integration of data from a variety of application, product, and third-party sources
• Establish and reinforce best practices around data governance, documentation, naming conventions, and maintainability
• Identify and drive opportunities to improve performance, scalability, and efficiency across our data systems
• Design efficient data workflows that query, transform, and deliver datasets to downstream systems and stakeholders
• Contribute to technical direction and architectural decisions as a senior member of the team
• Serve as a thought partner to teammates and cross-functional stakeholders on how to best leverage data across the business

Requirements:

• 5+ years experience in data engineering
• Strong SQL skills and experience building and optimizing data models for analytical use cases
• Experience building and maintaining reliable data pipelines in a modern cloud data environment
• Strong proficiency in Python or a comparable programming language commonly used in data engineering
• Experience building programmatic ETL/ELT pipelines using Python or similar tools to move and transform data across systems
• Experience working with data warehouses such as Snowflake
• Experience with transformation and orchestration tools such as dbt, Airflow, Dagster, or similar tools
• Strong understanding of data architecture, data modeling, and pipeline design best practices
• Ability to operate independently, prioritize effectively, and drive work forward in a fast-moving environment