Key Responsibilities
Contribute to the implementation of the data strategy of US Oncology analytics through new development and enhancements of existing products and processes.
Engage in the architectural discussions, implementation, and execution of newly migrated Databricks data ecosystem and all processes and projects that supports evolving data and analytics landscapes for The Network
Be responsible for creating/maintaining custom backend services to facilitate data and analytics products including using SQL, cloud development APIs, tools, and services.
Identify, design, optimize important process and implement scalable data pipelines and define best practices.
Develop and maintain callable data pipelines, data integration, and data quality frameworks to support growing data complexity
Create, analyze, and develop reliable and secure back-end functionalities to power the data-driven products.
Partner with cross-functional teams to implement the technical solutions to support the products for the analytics withing the larger US Oncology organization
Create data product documentation including robust data dictionaries and metadata tagging
Assist Data Analysts within the organization to understand the data model to support patient care and practice success
Minimum Requirement
Degree or equivalent and typically requires 4+ years of relevant experience.
Critical Skills
4+ years of relevant experience working in Data Engineering or Analytics Team.
4+ years of experience with databases preferably with Databricks or Snowflake.
4+ years of experience with ETL automation, SQL, RDMS for implementing scalable data transformation infrastructure..
3+ years of relevant development experience in object-oriented programming (Python) in an agile methodology
3+ years of experience with systems like ADLS/sFTP/Data Factory/Autoloader and developing data ingestion pipeline for flat files and using APIs
3+ years of relevant with various application architectures (Cloud Architecture, Modular Architecture)
2+ years of experience with DevOps activities for deploying pipelines using GitHub Actions or similar tools
Familiarity working with EHR or healthcare data or other complex data sets
Additional Knowledge & Skills
Familiarity with the Machine Learning Engineering, ML Ops and readiness to apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
is a plus
Working knowledge of report/dashboard development, data/report automation, self-service capabilities, data design, and integration, or data quality and governance preferred
Experience in managing and implementing successful projects
Familiarity with development tools such as JIRA, Asana, GitHub
Oncology and value-based care experience is a plus
Candidates must be authorized to work in USA.
Sponsosrship is not available for this role.
We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards.
This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets.
The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations.
In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered.
For more information regarding benefits at McKesson, please
Our Base Pay Range for this position
$105,500 - $175,900