chartis - Senior Data Platform Engineer (Observability)
Requirements
• 7+ years of experience in platform or data engineering roles, with a substantial portion focused on cloud infrastructure. • Hands-on experience with data catalog and metadata management platforms such as DataHub, Apache Atlas, or similar tools • Strong understanding of data observability, metadata management, data lineage, and data governance concepts. • Experience with cloud-based data warehouses (Snowflake or Databricks) and with orchestration tools (Azure Data Factory, Dagster, etc.) • Proficiency with Python • Working knowledge of data ingestion patterns, including batch processing and exposure to change data capture (CDC) concepts. • 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. • Strong communication skills with the ability to translate between technical and non-technical stakeholders. • Bachelor’s degree in a technology-related field of study (e.g. Computer Science, Health Informatics, Management Information Systems (MIS), Data Science, Analytics, etc.) • Salary range: $185,000 - $215,000, plus may be eligible for an annual discretionary bonus. The salary range for this role takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, skills, experience, training, licensure and certifications, practice area, and other business and organizational needs. In addition, Chartis offers several benefits including medical, dental, vision, HSA, FSA, disability insurance, life insurance, 401(k) match, paid time off, wellness stipend, and additional voluntary benefits.
Responsibilities
• Own the observability and search experience for the data platform, including the maintenance and evolution. Improve meta quality, lineage, and platform reliability to help users discover trusted data and make informed decisions with confidence. • Implement and operate orchestration and pipeline management solutions using modern data stack tools (e.g., Dagster, Astronomer / Airflow), with a focus on reliability, observability, and scalability. • Embed data lifecycle management into platform design, including retention, archival, and deletion controls aligned with regulatory obligations and client agreements. • Ensure data ingestion and storage architectures are compliant with healthcare regulatory requirements (e.g., HIPAA), including secure handling of PHI, audit logging, and encryption in transit and at rest. • Drive performance, reliability, and cost optimization across the data platform. • Build and maintain scalable Terraform modules and pipelines that provision and manage Azure infrastructure supporting both client-specific and reusable firmwide analytics, alongside Snowflake, dbt, and Python components of the stack. • Translate business, product, and client requirements into executable engineering plans, balancing near-term delivery needs with longer-term investments and collaborating closely with our Product Engineering, Analytics Delivery, and Security teams to align platform capabilities with firm priorities. • Support the continued development of data and analytics culture across Chartis through knowledge share, cross-functional training, and mentorship. • Mentor junior engineers and contribute to firmwide engineering standards around code quality, documentation, testing, and operational excellence.
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