The role involves designing and implementing scalable integrations between Databricks and key enterprise systems like Netsuite, Workday, and SalesForce, while developing automated data pipelines using low-code tools and custom AWS solutions. Responsibilities also include owning infrastructure provisioning via Infrastructure as Code (Terraform) and mentoring engineers on best practices.

The Senior Data Engineer will architect and design scalable, fault-tolerant data pipelines for complex healthcare data ingestion, transformation, and reporting, while leading technical decision-making for data infrastructure and tooling selection. Responsibilities also include mentoring junior engineers, establishing engineering best practices, and driving cross-functional collaboration with Data Science, BI, and Product teams.

The Senior Data Engineer will be responsible for building and architecting automation and observability for the EDAS platform, focusing on data consumption, automating workflows, and ensuring platform reliability through data-driven tools. This involves designing and implementing automation solutions, building observability frameworks for monitoring and alerting, optimizing data pipelines, and ensuring compliance with governance and security standards.

The Senior Data Engineer will design, build, and evolve reliable data pipelines and models using SQL, Python, and Databricks/Spark, focusing on sensitive customer data, identity resolution, and unifying disparate sources. Responsibilities also include improving existing pipelines, adding tests and documentation, and ensuring data privacy compliance.