Senior Data Engineer

It’s More Than a Career, It’s a Mission.

Our people are the foundation of our success. By joining our growing team at Sarah Cannon Research Institute (SCRI), a subsidiary of McKesson, you will have the opportunity to become part of one of the largest community-based cancer programs to advance oncology treatments and improve outcomes for cancer patients across the globe. We look for mission-driven candidates who have a desire to advance the fight against cancer and make a difference in the lives of patients diagnosed with cancer every day.

Our Mission

People who live with cancer – those who work to prevent it, fight it, and survive it – are at the heart of every decision we make. Bringing the most innovative medical minds together with the most passionate caregivers in their communities, we are transforming care and personalizing treatment. Through clinical excellence and cutting-edge research, SCRI is redefining cancer care around the world.

SCRI’s Data Solutions team is seeking a Senior Data Engineer to address strategic data needs. The Senior Data Engineer is responsible for designing, building, and maintaining data engineering processes. This role involves working with cross-functional teams to develop efficient data pipelines and support data modernization initiatives. The position requires expertise in data engineering principles, experience with cloud technologies, and an ability to deliver reliable data solutions. 

Duties and Responsibilities: 

• Design and implement scalable and efficient data pipelines to support various data-driven initiatives.  

• Designs and maintains Databricks Lakehouse pipelines across Bronze/Silver/Gold (Delta) layers, producing governed, ML-ready datasets with built-in data quality checks and lineage. 

• Collaborate with cross-functional teams to understand data requirements and contribute to the development of data architectures.  

• Work on data integration projects, ensuring seamless and optimized data flow between systems.  

• Implement best practices for data engineering, ensuring data quality, reliability, and performance.  

• Contribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflows.  

• Demonstrate technical leadership by staying abreast of emerging data engineering technologies and implementing industry best practices.  

• Provide technical leadership in enabling AI/ML initiatives by designing scalable, reliable, and well-governed data engineering solutions. 

• Effectively communicate technical concepts to both technical and non-technical stakeholders.  

• Promotions to different environments using GitHub CICD with GitHub Actions / Liquibase 

• Participate in the evaluation and identification of new technologies 

Minimum Qualifications:  

• Deep technical expertise in building and optimizing data pipelines and large-scale processing systems.  

• Deep technical expertise with Azure Cloud and Databricks.   

• Experience working with cloud solutions and contributing to data modernization efforts.  

• Strong programming skills (e.g.,SQL, Python, Pyspark or Scala) for data manipulation and transfor