Senior Data Engineer

Montefiore Health SystemPlaza, ND
Onsite

About The Position

The Senior Data Engineer role within the data engineering vertical will play a pivotal role at the forefront of our data and analytics technology transformation initiatives. We are seeking an expert senior data engineer to build, enhance, and support a wide variety of data pipelines integrating data feeds from diverse internal and external sources. You will enhance our suite of enterprise data products supporting business cases across the Montefiore health system. This role will work with complex data solutions in a fast-paced, rapidly evolving landscape, answering critical business and clinical questions. This role is critical to scaling our data and insights capabilities, empowering teams with actionable insights, and supporting our mission to improve Patient healthcare.

Requirements

  • BS Required
  • Minimum of 12+ years of rich experience in data engineering, modern data architecture patterns, developing and supporting high-volume data pipelines, while ensuring data availability and accuracy
  • At least 4+ years of solid experience in Snowflake development, and SQL is a must.
  • Experience with cloud-based ELT Toolsets like Matillion, dbt cloud and data transformation components using Python SDK
  • Expertise in translating complex clinical, operational, financial, and administrative datasets into enterprise-grade data products, data modeling techniques, and performance analysis & tuning.
  • Experience with AWS Cloud, S3, DevOps and Git management

Nice To Haves

  • 10+ years Preferred
  • Experience with EPIC Cogito Analytics stack (Clarity, Caboodle etc.) is preferred
  • Knowledge in healthcare preferably in a health system domain

Responsibilities

  • Design, build, and automate robust, scalable data pipelines for ingesting, transforming, and loading both structured and unstructured data from diverse internal and external data sources
  • Design, Develop and support data models and schemas to support data integration and analysis
  • Promote and uphold data engineering best practices, standards, and data governance throughout the organization.
  • Implement CI/CD pipelines and best practices for data engineering assets, supporting robust deployment, monitoring, and version control.
  • Design and implementation of rules-driven data quality components that support enhanced observability, transparency, and robust remediation workflows, enabling rapid identification and resolution of data issues
  • Collaborate with product managers, data scientists, BI developers, and application teams to understand data requirements and translate them into technical solutions
  • Mentor early-career team members, fostering collaboration, knowledge-sharing, and professional growth

Benefits

  • An assortment of insurance products and discount programs through Voluntary Benefits.
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service