Temporary - Data Engineer

The American Cancer Society is working to end cancer as we know it, for everyone. Our employees and 1.3 million volunteers raise the bar every day, creating a culture of diverse backgrounds and experiences to better serve our communities. This is a calling, and those who answer it find fulfillment in focusing their talents on our lifesaving mission.

About the role

We are seeking a skilled Data Engineer to join our mission-driven team in the fight against cancer. As a key member of ACS’s growing enterprise data practice, you will design, build, and optimize a modern data ecosystem leveraging Microsoft Azure, Snowflake, and Dbt. This role focuses on developing scalable, high-performance data pipelines and infrastructure to enable advanced analytics, machine learning, and research insights across the organization. You will collaborate with the Senior Director of Data, analytics engineers, and data scientists to establish and enforce best practices in data architecture, automation, and governance.

Responsibilities

• Design, develop, and orchestrate modern data pipelines and integrations (30%) – Architect and manage scalable data workflows using Azure Data Factory, Snowflake, dbt, and cloud orchestration tools such as Prefect.io or Airflow, ensuring high performance and reliability.
• Implement and manage cloud-based data infrastructure (20%) – Administer and optimize data environments in Microsoft Azure, including Cosmos DB, Snowflake, and related services, performing configuration, monitoring, and cost optimization.
• Develop and deploy advanced data engineering solutions (20%) – Utilize Python for complex data transformation, automation, and performance optimization within robust CI/CD pipelines with comprehensive unit testing and peer code reviews.
• Integrate data from diverse sources (10%) – Leverage ingestion platforms such as FiveTran, Rivery.io, or OpenFlow to streamline and automate data collection from internal and external systems.
• Collaborate with cross-functional teams (10%) – Partner with analytics engineers, data scientists, and business stakeholders to design and refine data models that power research, visualization, and machine learning initiatives.
• Support data governance, security, and documentation (10%) – Implement and enforce best practices for data security, access control, and compliance, including Snowflake user and instance management.

Requirements

• Bachelor's Degree in Computer Science, Engineering, Computational Biology, or equivalent experience.
• 3+ years of relevant work experience in building modern data pipelines, including ETL, cloud storage, reporting, and deployment.

Skills

• Advanced proficiency in cloud data engineering within Microsoft Azure, including services such as Azure Data Factory, Azure Databricks, and Cosmos DB; experience with Snowflake for data warehousing and administration.
• Strong expertise in SQL and Python, including development of complex ETL/ELT workflows, automation scripts, and performance-optimized data transformations.
• Hands-on experience with modern orchestration and ingestion platforms such as Prefect.io, Apache Airflow, FiveTran, Rivery.io, or OpenFlow, supporting automated and scalable data movement.
• Proven experience implementing CI/CD practices for data engineering—including automated testing, code reviews, version control (e.g., GitHub/GitLab), and deployment pipelines.
• Experience designing and managing large-scale, high-density data systems, including structured, semi-structured, and unstructured data such as genomics, imaging, and biospecimen datasets.
• Familiarity with BI and visualization tools (e.g., Power BI, Tableau, Looker) and the ability to translate complex research or analytic requirements into optimized data models.
• Strong understanding of healthcare and research data domains, including claims, electronic health records (EHR), survey, and clinical datasets; knowledge of data governance, compliance, and privacy standards (e.g., HIPAA).
• Demonstrated collaboration skills working with data scientists, analytics engineers, and researchers to deliver high-quality, reliable, and well-documented data solutions.

Schedule

• Availability and ability to work after hours, weekends, holidays, etc., as needed, including on-call responsibilities to fulfill job requirements.
• Occasional travel (10-15%) may be required for department or program/project meetings, vendor management, or enterprise workshops.

Pay

The starting rate is $45 to $48 per hour. The final candidate's relevant experience and skills will be considered before an offer is extended.

Benefits

• Generous paid time off policy.
• Medical, dental, and retirement benefits.
• Wellness programs.
• Professional development programs to enhance staff skills.

Further details on benefits can be found on our careers site at jobs.cancer.org/benefits.