Data Engineering Intern assisting with data projects and cloud solutions at Simmons Bank. Collaborating on data pipelines and gaining exposure to modern data engineering concepts.
About the role
- Staff Data Engineer on Real World Evidence team driving large-scale data initiatives. Collaborating with cross-functional teams to optimize data pipelines and improve healthcare outcomes.
Responsibilities
- Act as a self-starter who drives execution independently, taking ownership and initiative with minimal need for day-to-day direction.
- Lead high-visibility RWE projects, starting with claims data, and keep multiple initiatives moving by proactively unblocking teams.
- Own the end-to-end architecture for critical data assets, ensuring solutions are scalable, reliable, and aligned with H1’s long-term vision.
- Design, build, and optimize large-scale data pipelines (hundreds of TBs) for performance, reliability, and cost efficiency.
- Partner with Product, Data Science, and downstream engineering teams to align priorities, manage dependencies, and deliver high-value outcomes.
- Represent engineering in cross-functional forums, shaping roadmaps and reducing reliance on senior leadership for day-to-day decisions.
- Develop deep domain expertise and mentor other engineers, helping raise the technical bar and influence the evolution of our data products.
Requirements
- 8+ years as a software, data, or backend engineer building and operating scalable, production-grade systems.
- Experience with large-scale data processing (e.g., Spark/PySpark on EMR or similar) or scalable distributed backend systems, with the ability to quickly deepen expertise in our data stack (PySpark, EMR, Hudi/Delta).
- Strong proficiency in SQL, including writing and optimizing complex queries over large datasets.
- Strong programming experience in Python (or a modern language with the ability to quickly ramp up in Python).
- Experience designing systems or large-scale datasets/pipelines with attention to performance, reliability, and maintainability.
- Hands-on experience with modern engineering workflows and tooling such as Git, JIRA, and CI/CD systems (e.g., CircleCI).
- Comfort deploying and troubleshooting distributed workloads in cloud environments such as AWS EMR or Kubernetes.
- Experience with workflow orchestration or job scheduling tools (e.g., Airflow, Argo).
- Demonstrated ability to independently drive complex, cross-team technical initiatives and influence stakeholders without formal authority.
- Experience with streaming/messaging technologies (e.g., Kafka, Kinesis) nice to have
- Background in RWE, healthcare data, or other complex/regulated data domains is preferred
- Experience using AI-assisted coding tools (e.g., GitHub Copilot, Claude Code) to accelerate development while maintaining quality is encouraged
Benefits
- Full suite of health insurance options, in addition to generous paid time off
- Pre-planned company-wide wellness holidays
- Retirement options
- Health & charitable donation stipends
- Impactful Business Resource Groups
- Flexible work hours & the opportunity to work from anywhere
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