Senior Software Engineer – Data

Recruiting from Scratch is a specialized talent firm dedicated to helping companies build exceptional teams. They are seeking a Senior Software Engineer – Data to design and maintain scalable ETL and ELT pipelines for healthcare supply chain data, develop data platforms, and integrate machine learning models into production workflows.

Responsibilities:

• Design, build, and maintain scalable ETL and ELT pipelines that process complex healthcare supply chain data
• Develop data platforms that ingest, transform, and enrich structured and unstructured datasets from a variety of enterprise sources
• Architect and optimize AWS-based data infrastructure with a focus on reliability, scalability, and cost efficiency
• Build production-grade LLM-powered workflows for entity extraction, normalization, classification, matching, and enrichment
• Design evaluation systems, prompting frameworks, guardrails, and monitoring solutions that improve AI reliability and performance
• Integrate machine learning models into production data workflows, including training pipelines, batch processing, inference systems, and monitoring
• Partner closely with Product, Engineering, and Data Operations teams to deliver data solutions that support business and customer needs
• Develop tooling that enables domain experts to review, validate, and continuously improve data quality
• Drive improvements in pipeline performance, observability, testing, and operational excellence
• Mentor engineers and contribute to architectural decisions, code reviews, and engineering best practices

Requirements:

• 4+ years of professional software or data engineering experience, including at least 3 years focused on data engineering
• Strong Python and SQL expertise with experience building production-grade data platforms
• Experience designing and operating large-scale ETL/ELT systems and workflow orchestration frameworks
• Hands-on experience with AWS services such as S3, Glue, Athena, Lambda, Redshift, or related cloud-native data technologies
• Strong understanding of data modeling, schema design, data warehousing, and data quality practices
• Experience integrating LLMs, AI models, or machine learning workflows into production systems
• Familiarity with prompt engineering, evaluation frameworks, structured outputs, caching strategies, and AI system reliability
• Ability to work independently in a remote environment while collaborating effectively across technical and non-technical teams
• Strong communication skills and ability to explain technical concepts clearly
• Experience within healthcare, healthcare supply chain technology, healthcare data platforms, or enterprise SaaS environments
• Experience with Rust for high-performance data processing applications
• Familiarity with master data management, data governance, and large-scale data quality initiatives
• Experience with NLP, information extraction, entity resolution, record linkage, embeddings, retrieval systems, or RAG architectures
• Experience working with large-scale web scraping, data ingestion, or heterogeneous data sources
• Familiarity with MLOps and LLMOps tooling, including prompt versioning, model evaluation, observability, and vector databases
• Experience with CI/CD, infrastructure-as-code, containerization, and production data platform operations
• Startup experience and comfort working in highly autonomous environments