Senior Data Engineer

Role overview

Design and operate data systems that make reliable information available for clinical, operational, analytical, and reporting work. This senior role shapes scalable data architecture and pipelines, improves platform performance and governance, and provides technical guidance across teams.

Responsibilities

- Design and build dependable data pipelines and reusable engineering patterns for varied organizational needs. - Automate data ingestion, transformation, and orchestration using cloud and open-source tools. - Optimize storage and processing in data lakes and cloud warehouses, including Azure and Databricks environments. - Monitor batch and streaming workflows for accuracy, consistency, and timely delivery; maintain documentation and lineage. - Integrate APIs, third-party systems, and structured or semi-structured data into shared platforms. - Partner with analysts, data scientists, engineers, and business stakeholders; review work, mentor colleagues, and identify improvements to cost, performance, and automation.

Requirements

- At least five years of data engineering experience building production-grade, cloud-based pipelines. - Strong skills in Databricks, SQL, dbt, Python, and cloud data ecosystems such as Azure. - Experience handling structured and semi-structured data from diverse domains. - Familiarity with CI/CD, orchestration tools such as Airflow or Azure Data Factory, and modern software engineering practices. - Strong analytical and problem-solving ability, including designing scalable responses to complex data needs.

Benefits and work setup

- Remote within the United States, with occasional planned travel under 10%. - Listed annual pay range: $120,000–$160,000 for full-time team members. - Benefits for US full-time employees include paid time off and holidays, employer-paid medical, dental, and vision options, HSA and FSA plans, disability coverage, and a 401(k) with company match.