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MedScout · 8 hours ago

Data Engineer

United States

Full-time

Remote

Mid Level

3+ years exp

MedScout is dedicated to empowering MedTech commercial teams with essential data and tools for medical innovations. As a Data Engineer, you'll design and maintain scalable data pipelines, integrate multiple data sources, and collaborate with cross-functional teams to drive business decisions through actionable insights.

Health CareMedicalSalesSoftware

Responsibilities

You will design, implement, and maintain scalable data pipelines to process large volumes of healthcare claims data using Databricks, Python, and PySpark, ensuring high data quality and performance optimization for downstream analytics

You will develop processes to integrate multiple data sources, including healthcare claims databases, into a unified data model that powers MedScout's sales enablement platform

You will work with Product, Customer Success, and Sales leaders to understand what our customers are looking to achieve with our platform and use those insights to inform and validate your thinking as you make design and implementation decisions

You will collaborate with data scientists and analysts to implement data transformations that support efficiently delivering advanced analytics, market insights, and predictive modeling capabilities for the platform

You will troubleshoot and resolve complex data pipeline issues, optimize system performance, and contribute to the continuous improvement of MedScript's data infrastructure and engineering practices

You will optimize workloads and cluster configurations to reduce compute costs while maintaining performance, including implementing auto-scaling policies, right-sizing clusters, and monitoring resource utilization patterns

Qualification

DatabricksPythonPySparkSQLData modelingData transformation toolsData quality frameworksVersion control (Git)CI/CDInfrastructure as codeHealthcare claims data

Required

3+ years of experience building, maintaining, and operating data pipelines in a modern data warehouse like Databricks, Snowflake, BigQuery, or AWS Redshift

Strong Python, SQL and PySpark skills

Experience with data transformation tools like DBT or SQLMesh

Solid understanding of data modeling and schema design, particularly in contexts involving complex relationships and high-volume data processing

Experience with data quality frameworks, including automated testing, validation, and monitoring of data pipelines

Familiarity with modern software development practices including version control (Git), CI/CD, and infrastructure as code

Ability to work effectively with cross-functional teams, translating business requirements into technical specifications and communicating complex technical concepts to non-technical stakeholders