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Remote option, metro Bangalore, mid-level generalist data title, and broad toolset create high applicant density.
Core data engineering skills are transferable, but LLM and clinical-data preferences raise domain specificity to medium.
Explicit 5+ years plus mandatory Snowflake, Airflow, SQL, AWS and LLM/tooling experience enforces high filtering.
Design, develop, and maintain scalable data platforms and software architectures that support clinical trial operations and business intelligence.
Build and integrate LLM-powered solutions (e.g., RAG pipelines, intelligent agents) using AI-assisted tools and AWS services like Bedrock.
Collaborate across SDLC phases with cross-functional teams to deliver high-quality, data-driven solutions including data pipelines, ETL workflows, and production support.
Bachelor’s or higher degree in Computer Science, IT, or related technical field.
5+ years of experience in software engineering, data engineering, or data-focused development roles.
Strong proficiency in Python (including Flask, pandas, NumPy) and advanced SQL across Oracle, MS SQL Server, PostgreSQL, and/or Snowflake.
Experience with AWS cloud services (S3, EC2, Lambda, Bedrock) and AI-assisted development tools (GitHub Copilot, LangChain).
Experienced in designing and optimizing complex SQL queries, data architectures, and ETL pipelines in clinical or data-intensive environments.
Demonstrates end-to-end ownership through all SDLC phases, from requirements gathering to deployment and production support.
Proficient in developing LLM-powered applications and integrating them with scalable cloud infrastructure, showing strong analytical and problem-solving skills.