Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field; Master's degree preferred.
Minimum of three years in data engineering, systems engineering or a related technical role.
Experience in developing data platforms and pipelines, particularly cloud-based solutions.
Proficiency in SQL and at least one programming language (e.g., Python).
Familiarity with DataOps or MLOps practices and CI/CD pipelines.
Responsibilities
Design, build, and maintain data platforms and services for research and analytics.
Develop scalable data architectures using modern data warehouse/lakehouse patterns.
Implement ETL/ELT workflows with data validation and quality monitoring.
Support reproducible analytics and ML pipelines with best practices for monitoring.
Collaborate with stakeholders to translate research requirements into technical solutions.
Document systems and workflows clearly to support transparency and reuse.
Benefits
Work with diverse professionals in the healthcare industry.
Free parking.
Paid holidays, vacation, and sick time.
Group Life and Voluntary Term Life insurance.
Long-term and Short-term Disability plans.
Employee Assistance Program (EAP).
Flexible Spending Account (FSA).
403b Retirement Plan with employer contributions.
Fitness program.
Pet insurance.
Full Job Description
Position Summary
The Data Systems / Solutions Engineer serves as a key technical contributor within the Regenstrief Data Services team, functioning as a full-stack DataOps/MLOps engineer supporting research and analytics initiatives. This role is responsible for designing, building, and maintaining scalable, reliable data systems and pipelines that enable high-quality data ingestion, transformation, storage, and analysis.
The position emphasizes the development of robust, secure, and reproducible data infrastructure that supports data science, analytics, and AI-driven research. The Engineer applies modern software engineering and data engineering practices to ensure data assets are accessible, well-governed, and aligned with clinical and research requirements.
This position is a hybrid position with at least one (1) to two (2) days of onsite activity based on business needs. This position is located in downtown Indianapolis IN.
Essential Duties and Responsibilities
Data Systems Engineering and Operations:
Design, build, and maintain data platforms, pipelines, and services that support research, analytics, and AI/ML workloads.
Develop and maintain scalable data architectures using modern data warehouse/lakehouse patterns.
Ensure data systems are reliable, performant, and designed for long-term sustainability.
Implement and maintain ETL/ELT workflows, data validation, and quality monitoring processes.
DataOps / MLOps Enablement:
Implement CI/CD practices for data and ML workflows, including testing, version control, and environment promotion.
Support reproducible analytics and ML pipelines, including experiment tracking and model lifecycle considerations.
Apply best practices for monitoring, observability, and incident response across data systems.
Cloud, Security, and Governance
Design and maintain cloud-based data solutions using secure and scalable architectural patterns.
Apply data governance, access control, and auditing practices consistent with HIPAA-aligned research environments.
Ensure appropriate handling of sensitive data through de-identification, access management, and compliance controls.
Optimize performance and cost efficiency across compute and storage resources.
Clinical and Research Data Support
Work with clinical and research stakeholders to translate domain requirements into technical solutions.
Support integration and use of clinical and biomedical data standards (e.g., EHR data, HL7/FHIR, OMOP).
Produce well-documented data assets and technical specifications to support reuse and transparency.
Collaboration and Project Support
Collaborate with data engineers, researchers, analysts, and project managers to deliver high-quality solutions.
Contribute to project planning, estimation, and execution.
Serve as a technical resource to team members and stakeholders.
Document systems, workflows, and architectural decisions clearly and consistently.
Continuous Learning and Innovation
Maintain current knowledge of emerging tools, technologies, and best practices in data engineering and AI.
Leverage AI-assisted development tools responsibly to improve productivity and code quality.
Participate in continuous improvement efforts across systems, processes, and workflows.
Knowledge, Skills, and Abilities
Technical Knowledge:
Proficiency in modern data engineering concepts, including:
Data warehouse and lakehouse architectures
Dimensional modeling and data transformation patterns
SQL and at least one general-purpose programming language (e.g., Python)
Experience with CI/CD pipelines and automated testing for data and ML workflows
Familiarity with data quality frameworks, lineage tracking, and observability tools
Understanding of cloud platforms, identity and access management, and security best practices
Knowledge of clinical and biomedical data standards and research workflows preferred
Analytical and Problem-Solving Skills
Ability to analyze complex technical problems and implement effective solutions
Strong troubleshooting skills across data ingestion, transformation, and delivery layers
Ability to balance reliability, performance, and cost considerations
Communication and Collaboration
Strong written and verbal communication skills
Ability to document technical concepts clearly for both technical and non-technical audiences
Demonstrated ability to collaborate effectively in multidisciplinary teams
Education and Experience
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field required; Master's degree preferred.
Minimum of three (3) years of professional experience in data engineering, systems engineering, or a related technical role.
Demonstrated experience in:
Data platform or data pipeline development
Cloud-based data system
SQL and programmatic data processing
DataOps or MLOps practices
Performance Expectations
Works independently within established guidelines and best practices.
Produces high-quality work with minimal supervision.
Demonstrates sound judgment and attention to detail.
Contributes to continuous improvement of tools, processes, and team effectiveness.
Physical Demands
Ability to work standard business hours with flexibility as needed.
Ability to sit or stand for extended periods.
Ability to operate a computer and standard office equipment.
Ability to lift and move materials up to 20 pounds as needed.
Ability to travel occasionally for meetings or training.
Work Environment
Hybrid office and research environment.
Fast-paced, deadline-driven setting.
Requires collaboration with internal teams and external partners.
Regular use of computers, communication tools, and office equipment.
BENEFITS OF WORKING HERE
Work with a variety of diverse professionals in the healthcare industry
Free parking
Paid holidays, vacation, and sick time
Group Life and Voluntary Term Life insurance
Long-term and Short-term Disability plans
Employee Assistance Program (EAP)
Flexible Spending Account (FSA)
403b Retirement Plan with gracious employer contributions
Fitness program
Pet insurance
Qualified employer for loan forgiveness
Please note sponsorship and/or relocation are not available for this position.
