Research Application Support Engineer - Remote
At the American Cancer Society, we're working to end cancer as we know it, for everyone. Our employees and 1.3 million volunteers are raising the bar every single day. We are a culture comprised of diverse backgrounds and experience, to better serve our communities.
The people who work at the American Cancer Society focus their diverse talents on our lifesaving mission. It is a calling. And the people who answer it are fulfilled.
***This is a remote position that can be home-based anywhere within the United States***
ESSENTIAL FUNCTIONS:
Data Platform Support 25%
Provide advanced technical support for SaaS platforms and analytics tools, resolving data issues—including user login access problems—and ensuring seamless integration with enterprise data systems. Collaborate with vendors and internal teams to quickly address platform, user access, and data challenges. Examples include but are not limited to SAS, SAS Studio, SAS Callable Sudaan, Manifold Science Cloud, R and R Studio, and several government analytical platforms and databases.
Data Pipeline and Transformation Engineering 25%
Provide ongoing support for scalable data pipelines that enable analytics, modeling, and reporting. Maintain and troubleshoot data pipelines to keep analytics and reporting running smoothly. Ensure large datasets are processed reliably, quickly fix any issues, and collaborate with teams to make data easy to use and queries run efficiently. Support may include advising IT team members and business stakeholders regarding alternative ways to use existing ACS technology or considerations regarding future investments.
Data Quality, Governance, and Documentation 20%
Proactively monitor server availability to ensure systems remain operational and address any downtime or disruptions promptly. Develop and maintain robust disaster recovery solutions to protect data integrity, minimize the impact of system failures, and ensure rapid restoration of services in the event of unexpected incidents. Create comprehensive technical documentation for IT support, including detailed records of data models, pipelines, server environments, and transformation workflows. Documentation should facilitate system maintenance, knowledge transfer, and business continuity across IT and other teams. Given their work in data science, code, and configuration, assist business, where needed, in following ACS and industry best practices related to software development lifecycle.
Data Modeling Troubleshooting and Support 15%
Support and troubleshoot large data models within advanced analytics platforms and optimize execution performance of statistical and analytical workloads (runtime, memory usage) to enhance overall performance with complex data. Diagnose errors within data pipelines and transformation logic and implement improvements that increase model scalability for large datasets.
Analytics Enablement & Stakeholder Collaboration (15%)
Work collaboratively with various IT and business stakeholders to ensure reliable access to trusted data for analytics and business users. Support Discovery pillar by troubleshooting and resolving issues promptly.
EXPERIENCE/QUALIFICATIONS:
- Minimum Degree Required: Bachelor's Degree in Computer Science, Engineering, or equivalent experience
- Preferred Degree: Choose an item.
- Certificate(s) or License(s):
- Years of experience: 3-5 years of relevant experience, 3+ years of experience with supporting, monitoring, troubleshooting data pipelines including the ETL, cloud-storage, reporting, and deployment. SAS or R /R Studio experience preferred.
KNOWLEDGE, SKILLS, AND ABILITY:
- Proficiency in cloud-based data engineering, preferably within Microsoft Azure, including services such as Azure Data Factory, Azure Databricks, and familiarity with other cloud platforms (AWS, GCP) a plus.
- Strong experience with R / RStudio (large data model troubleshooting), SAS, SQL and Python, including data manipulation, transformation, and automation in support of scalable data pipelines.
- Additional platforms/software where experience is considered a plus: SPSS, EndNote, JoinPoint, DevCan, ArcGIS, Origin, Streetsmart, MatLab, Social Explorer, Traveltime, Tableau, Stata
- Hands-on experience with modern data warehousing and transformation tools, including Snowflake and Dbt, for building reliable, maintainable data models.
- Familiarity of CI/CD practices and version control (e.g., Git, GitHub/GitLab) as part of modern data engineering workflows, including automated testing and deployment.
- Understanding of data quality and privacy, governance, and documentation best practices, ensuring accuracy, consistency, and compliance across data assets.
- Experience or familiarity with healthcare or research data (e.g., clinical, claims, EHR, biospecimen, genomic, or imaging data) preferred.
- Excellent business relationship and communication skills, with the ability to collaborate effectively across various teams and convey complex information clearly to both technical and non-technical stakeholders.
TRAVEL REQUIREMENTS:
- Occasional travel- 10-15% - may be required for department or program/project meetings, vendor management, or enterprise workshops.
PHYSICAL REQUIREMENTS:
- Availability and ability to work after hours, weekends, holidays, etc. as needed, to be on call and/or to fulfill job responsibilities and requirements.
The starting rate is $82,000 to $102,000 annual. The final candidate's relevant experience/skills will be considered before an offer is extended. Actual starting pay will vary based on non-discriminatory factors including, but not limited to, geographic location, experience, skills, specialty, and education.
ACS provides staff a generous paid time off policy; medical, dental, retirement benefits, wellness programs, and professional development programs to enhance staff skills. Further details on our benefits can be found on our careers site at: jobs.cancer.org/benefits. We are a proud equal opportunity employer.
Skills Required
- Bachelor's degree in Computer Science, Engineering, or equivalent experience
- 3-5 years relevant experience supporting, monitoring, and troubleshooting data pipelines (ETL, cloud storage, reporting, deployment)
- Proficiency in cloud-based data engineering, preferably Microsoft Azure (Azure Data Factory, Azure Databricks)
- Strong experience with R / RStudio, SAS, SQL, and Python for data manipulation, transformation, and automation
- Hands-on experience with modern data warehousing and transformation tools including Snowflake and dbt
- Familiarity with CI/CD practices and version control (Git, GitHub/GitLab)
- Understanding of data quality, privacy, governance, and documentation best practices
- Excellent business relationship and communication skills; ability to collaborate across technical and non-technical teams
- Availability to work after hours, weekends, holidays and be on-call as needed
- Experience or familiarity with healthcare or research data (clinical, claims, EHR, biospecimen, genomic, imaging)
- Experience with additional analytics platforms/software (SPSS, EndNote, JoinPoint, DevCan, ArcGIS, Origin, Streetsmart, MatLab, Social Explorer, Traveltime, Tableau, Stata)
What We Do
Grupo ACS is a global leader in infrastructure development, specializing in engineering, construction, and the management of critical assets across various sectors.









