Research Application Support Engineer - Remote

Essential Functions

• Data Platform Support (25%)
• Provide advanced technical support for SaaS platforms and analytics tools.
• Resolve data issues including user login access problems.
• Ensure seamless integration with enterprise data systems.
• Collaborate with vendors and internal teams to address platform, user access, and data challenges.
• Examples include 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%)
• Ongoing support for scalable data pipelines enabling analytics, modeling, and reporting.
• Maintain and troubleshoot data pipelines to keep analytics and reporting running smoothly.
• Ensure large datasets are processed reliably and quickly fix any issues.
• 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.
• 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.
• Avoid assisting 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.
• Optimize execution performance of statistical and analytical workloads (runtime, memory usage).
• 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: Not specified.
• Certificate(s) or License(s): Not specified.
• 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 Abilities
• 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.

Compensation

• 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.

Benefits

• 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.

Equal Opportunity Employer

• We are a proud equal opportunity employer.