The Data Engineer I will support the design, development, and maintenance of data pipelines and workflows, assisting in data integration and transformation using tools like Python, T-SQL, SSMS, and Databricks. The role involves collaborating with other Data Engineers, working with healthcare data sets, translating business requirements into technical specifications, and participating in code reviews.
Reporting into the Market Access and Custom Analytics organization, this role will be a part of the MACA Solutions team that works closely with MACA Solutions Manager to develop consulting enablement tools and processes for MACA regional teams to utilize in their work with internal and external customers. Specifically, helping to drive market adoption and optimize da Vinci minimally invasive robotic assisted surgery.
Design, scalable software systems with a focus on quality, performance, and maintainability. Lead systems architecture decisions, ensuring the design aligns with business requirements and technical standards. Collaborate with Research Leads, Product Owners to gather requirements, design ML systems and coordinate the software delivery. Create and maintain documentation for the different initiatives the team is participating in.
A DB2 Architect responsible for managing and maintaining IBM DB2 databases, ensuring that they are running efficiently and securely. Knowledge of integration of DB2 databases on various platforms. Proficiency in writing complex SQL queries and optimizing SQL Queries for finetuning performance issues. Knowledge of normalization, data modeling, Load management, and suggesting best practices for DB2 schema design.
In this pivotal role as Data Project Manager, you will drive Agile ceremonies and team productivity while fostering a collaborative environment focused on building scalable data pipelines and analytics tools to support clinical operations. The ideal candidate brings a deep understanding of Agile principles, excels in team facilitation, and has hands-on experience supporting data engineering teams working with Python, SQL, Databricks, and the Azure cloud ecosystem.