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Strong employer brand, mid-level role, and Hyderabad metro presence increase candidate competition.
Core data engineering and cloud skills are highly transferable across industries despite healthcare-preferred experience.
Explicit 5–8 years requirement plus SME-level Databricks, AWS, LLMs, and CI/CD/IaC makes filtering strict.
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Design, build, and maintain scalable batch, streaming, and real-time data pipelines and analytics-ready data products using Databricks, AWS, and cloud-native technologies.
Develop and deploy AI-powered solutions including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents using frameworks like LangChain and AutoGen.
Lead engineering standards, implement CI/CD pipelines, data governance, and collaborate with cross-functional teams to deliver business-driven solutions.
5-8 years of hands-on experience in Data Engineering, Software Engineering, or Cloud Data Platforms.
Expertise in Databricks and AWS Data & Analytics ecosystem including Glue, Lambda, S3, Athena, Redshift, and Lake Formation.
Proficiency in Python, PySpark, SQL, and distributed data processing frameworks.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
Demonstrated experience working in Agile, product-oriented environments with end-to-end ownership over data engineering and AI initiatives.
Strong background in modern Lakehouse architectures and enterprise-scale data pipelines on cloud platforms like AWS or Azure.
Ability to lead complex technical initiatives, mentor teams, and innovate using AI-assisted development and Agentic AI orchestration frameworks.