Senior Data Platform Engineer (Orchestration)

Join Chartis, a leading healthcare consulting firm, as a Senior Data Platform Engineer. In this hands-on role, you will be responsible for building, scaling, and operating the Data Platform infrastructure that underpins our advisory work. You will design, deploy, and maintain data asset management pipelines, ensuring compliance with healthcare regulatory requirements. You will also drive performance, reliability, and cost optimization across the data platform, and mentor junior engineers. This is an exciting opportunity to make a meaningful impact in the healthcare industry.

• Design, deploy, and maintain data asset management pipelines utilizing Airflow or Dagster, ensuring reliability, observability, and scalability.
• Implement and operate orchestration and pipeline management solutions using modern data stack tools, focusing on performance, reliability, and cost optimization.
• Build and maintain scalable Terraform modules and pipelines that provision and manage Azure infrastructure supporting both client-specific and reusable firmwide analytics.
• We’re looking for collaborative, creative problem solvers with a strong desire to materially improve the delivery of healthcare. You are a doer who is comfortable operating in small, early-stage teams where everyone is hands-on
• Hands-on experience with data catalog and metadata management platforms such as DataHub, Apache Atlas, or similar tools
• 7+ years of experience in platform or data engineering roles, with a substantial portion focused on cloud infrastructure
• Strong understanding of data observability, metadata management, data lineage, and data governance concepts
• Working knowledge of data ingestion patterns, including batch processing and exposure to change data capture (CDC) concepts
• Exposure to healthcare data or familiarity with core healthcare data concepts (e.g., claims, clinical, operational data) is preferred; deep domain expertise is not required
• Strong communication skills with the ability to translate between technical and non-technical stakeholders
• Experience establishing engineering standards, CI/CD practices, and observability for data platforms
• Experience building and scaling components of data platforms that support self-service analytics and multiple downstream consumers
• Experience with cloud-based data warehouses (Snowflake or Databricks) and with orchestration tools (Azure Data Factory, Dagster, GitHub Actions, etc.)
• Deep hands-on experience with a modern data orchestration tool such as Airflow, Dagster, or similar tools
• Bachelor’s degree in a technology-related field of study (e.g. Computer Science, Health Informatics, Management Information Systems (MIS), Data Science, Analytics, etc.)
• Enthusiasm and a desire for continuous learning in a fast-paced, entrepreneurial environment