Sarah Cannon Research Institute (SCRI) seeks a Data Ops Engineer to join our mission-driven team. In this role, you will support strategic data initiatives by designing, constructing, and maintaining our data architectures and large-scale processing systems. You will collaborate with cross-functional teams to develop efficient data pipelines and contribute to data modernization efforts that advance our work in oncology.
What You'll Do
- Design and implement scalable and efficient data pipelines to support various data-driven initiatives.
- Collaborate with cross-functional teams to understand data requirements and contribute to the development of data architecture.
- 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.
- Create and maintain technical documentation, including data mapping documents, solution design documents, and data dictionaries.
- Effectively communicate technical concepts to both technical and non-technical stakeholders.
- Manage automation and promotions to different environments using GitHub CI/CD with GitHub Actions and Liquibase.
- Participate in the evaluation and identification of new technologies.
What We're Looking For
- 5+ years of experience in data engineering.
- Bachelor's degree in a related field (e.g., Computer Science, Information Technology, Data Science), or related experience.
- Technical expertise in building and optimizing data pipelines and large-scale processing systems.
- Technical expertise with Azure Cloud, Data Factory, Batch Service, and Databricks.
- Experience working with cloud solutions and contributing to data modernization efforts.
- Experience using Terraform and bicep scripts to build Azure infrastructure.
- Experience implementing security changes using Azure RBAC.
- Experience building cloud infrastructure including Data Factory, Batch Service, Azure Gen 2 Storage Account, and Azure SQL database.
- Experience developing data pipelines through proficiency in programming languages such as SQL, Python, Pyspark, or Scala.
- Excellent understanding of data engineering principles, data architecture, and database management.
- Strong problem-solving skills and attention to detail.
- Excellent communication skills, with the ability to convey technical concepts to both technical and non-technical stakeholders.
Nice to Have
- Knowledge of the healthcare, distribution, or software industries.
- Strong technical aptitude and experience with a wide variety of technologies.
- Ability to rapidly learn and, if required, evaluate a new tool or technology.
- Strong verbal and written communication skills.
- Demonstrated technical experience.
- An innovative thinker.
- A strong customer and quality focus.
Technical Stack
- Cloud: Azure Cloud, Azure Data Factory, Azure Batch Service, Databricks
- Infrastructure as Code: Terraform, Bicep
- Security & Storage: Azure RBAC, Azure Gen 2 Storage Account, Azure SQL Database
- Languages & Data Processing: SQL, Python, Pyspark, Scala
- CI/CD & Data Management: GitHub Actions, Liquibase
Team & Environment
You will join the Data Solutions team, collaborating with cross-functional groups on strategic data initiatives.
Benefits & Compensation
- Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
