Data Engineer building scalable data platforms using Databricks and Azure for Reconomy. Collaborating across teams to deliver high - quality data solutions.
About the role
- Senior Engineer contributing to Proscia’s Real World Data business and scaling AI systems for cancer research. Collaborating with cross-functional teams to align technical strategy and integrate solutions.
Responsibilities
- Build and deploy LLM-enabled data products/workflows that turn structured + unstructured inputs into curated, research-ready outputs.
- Develop and refine data pipelines and warehouse layers (raw → curated → marts) to support both analytics and AI workflows.
- Implement LLMOps/MLOps foundations: evaluation, versioning, monitoring/observability, and safe release processes for model/prompt changes.
- Deliver traceable and reproducible outputs (evidence references, run metadata, input/version tracking).
- Identify and implement process improvements—automation, reliability controls, and quality checks—to accelerate delivery and reduce manual effort.
- Collaborate with core engineering, AI, and RWD stakeholders to align technical strategy and integrate solutions into the broader Proscia platform.
Requirements
- Strong experience building production systems in Python.
- Demonstrated experience delivering GenAI/LLM solutions into production (beyond experimentation)
- Experience owning the LLM lifecycle in production: prompt/model versioning, evaluation/regression testing, monitoring, and controlled releases.
- Experience shipping an LLM-enabled workflow end-to-end (design → build → deploy → operate).
- Solid fundamentals in SQL, data modeling, and data warehouse patterns.
- Experience with Snowflake or similar platforms.
- Software engineering practices: unit/integration testing, CI/CD, and containerization (Docker; Kubernetes).
- Experience with cloud platforms (AWS preferred).
Benefits
- Comprehensive benefits
- Flexible schedules
- Insurance options
Job title
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Degree requirement
Tech skills
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