Databrick Engineer - Python, Pyspark, Apache Spark, SQL

We have a 6 - 9 month contract, with potential for contract to hire for a skilled Data Engineer to design, build, and optimize scalable data pipelines and automation for analytics solutions in a modern cloud-based environment. This role is highly hands-on and will focus on developing reliable, performant data workflows using Spark, Python, SQL, and Databricks, while following strong software engineering best practices. You’ll collaborate closely with data scientists, analytics teams, and platform engineers to deliver high-quality data solutions that support reporting, analytics, and machine learning initiatives. The position is remote • MUST HAVES: • 3 or more years of experience in Spark • 3 or more years of experience in Python • 3 or more years of experience in SQL • 5 or more years of experience in software engineering (unit tests, integration tests, GitHub, dependency management, CI/CD) • 3 or more years of experience in Databricks • Healthcare Data background • Automation • Preferred Experience:3 or more years of experience with PySpark • Git and MLOps best practices • About this Role: Focused on foundational work supporting the data solutions initiatives • Key Responsibilities: Design, develop, and maintain scalable data pipelines using Apache Spark and Databricks • Build and optimize data transformations using Python, PySpark, and SQL • Ensure data quality, reliability, and performance across batch and streaming workloads • Apply strong software engineering best practices, including unit testing, integration testing, and code reviews • Manage source control using GitHub and participate in CI/CD workflows • Collaborate with cross-functional teams to support analytics and ML use cases • Troubleshoot and resolve data pipeline and performance issues