Your Role
The Data Services team is responsible for technical design and end-to-end delivery of complex data-driven solutions and data products for the enterprise. The Data Engineer,Senior will report to the Sr Manager, Data Solutions / Manager. This role is responsible for independent designing, building, and operating complex data pipelines and cloud data solutions while embedding security, automation, and reliability throughout the software development lifecycle (SDLC). The Senior Data Engineer plays a critical role in ensuring production readiness, operational excellence, and adherence to engineering standards across data products.
This role is a hands‑on technical leader who thrives in a collaborative environment, contributes to engineering best practices, and actively supports continuous improvement across people, process, and technology.
Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow - personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.
Your Knowledge and Experience
Requires a bachelor's degree or equivalent experience.
Requires a minimum of 5 years of relevant data engineering experience.
Strong hands‑on experience with SQL, including scripting and automation
Expertise with cloud platforms (Azure preferred) and services such as ADLS, Synapse, and Data Factory
Hands‑on experience with modern data stack tools such as dbt, Snowflake, Databricks, Airflow, or Tidal
Solid knowledge of data modeling (Data Vault 2.0), data integration, data architecture, warehousing, and data quality
Experience implementing CI/CD pipelines (e.g., Bitbucket, GitHub)
Strong understanding of agile delivery methodologies and enterprise cloud integration
Excellent communication skills with the ability to translate technical solutions to non‑technical stakeholders
Experience in healthcare or regulated environments, including Epic ecosystem exposure in preferred.
Awareness of data governance, security standards, and production certification processes
#LI-FB1
Your Work
In this role, you will:
Design, build, and maintain complex, data pipelines from development through production for multiple use cases
Develop efficient, scalable, and cost‑effective implementations, leveraging reusable frameworks and patterns
Integrate security, automation, and quality controls throughout the SDLC using DevSecOps best practices
Drive operational excellence, including incident management, root cause analysis, and deployment stability
Leverage AI‑assisted approaches across development, testing, and deployment to reduce operational overhead and improve quality
Monitor and manage software configuration changes to proactively address data reliability and customer experience issues
Coordinate sustaining support for multiple data platforms or business processes within a cloud environment
Perform monitoring, tuning, and optimization of data pipelines to ensure performance, availability, and efficient resource utilization
Implement and maintain automated testing, validation, and monitoring frameworks for data workflows
Work within an agile / DevSecOps pod model alongside solution leads, data modelers, analysts, and business partners
Provide technical expertise to translate complex functional requirements into robust technical designs
Mentor and support Data Engineers through code reviews, knowledge sharing, and engineering guidance
Apply domain knowledge of healthcare and enterprise IT trends to inform solution delivery
Your Work
In this role, you will:
Design, build, and maintain complex, data pipelines from development through production for multiple use cases
Develop efficient, scalable, and cost‑effective implementations, leveraging reusable frameworks and patterns
Integrate security, automation, and quality controls throughout the SDLC using DevSecOps best practices
Drive operational excellence, including incident management, root cause analysis, and deployment stability
Leverage AI‑assisted approaches across development, testing, and deployment to reduce operational overhead and improve quality
Monitor and manage software configuration changes to proactively address data reliability and customer experience issues
Coordinate sustaining support for multiple data platforms or business processes within a cloud environment
Perform monitoring, tuning, and optimization of data pipelines to ensure performance, availability, and efficient resource utilization
Implement and maintain automated testing, validation, and monitoring frameworks for data workflows
Work within an agile / DevSecOps pod model alongside solution leads, data modelers, analysts, and business partners
Provide technical expertise to translate complex functional requirements into robust technical designs
Mentor and support Data Engineers through code reviews, knowledge sharing, and engineering guidance
Apply domain knowledge of healthcare and enterprise IT trends to inform solution delivery