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Mid-level, popular Data Engineer role in metro with broad tech stack increases candidate competition.
Core data engineering skills transfer across industries, though healthcare preference increases domain specificity.
Explicit 5+ years and many mandatory cloud, platform, and data engineering skills create strict filters.
Design, develop, and maintain scalable enterprise data pipelines and processing frameworks primarily using Snowflake, Azure, Apache Spark, Databricks, and Airflow.
Optimize data platform performance, scalability, and security specifically for healthcare data involving compliance and governance.
Support AI/ML workflows and model deployment integration while collaborating with analytics, data science, and business teams.
Bachelor’s degree in Computer Science, Engineering, IT, Data Science, or related field.
Minimum 5 years of experience in Data Engineering roles focusing on enterprise-scale data pipelines and cloud-based distributed processing.
Strong technical skills with Snowflake, Azure, Apache Spark, Databricks, Python, SQL, Airflow, Kubernetes, and CI/CD tooling (GitHub).
Work location requirement: Hybrid remote position based in Noida, Uttar Pradesh.
Experienced operating in enterprise-level healthcare data environments with knowledge of healthcare data standards and security compliance.
Proficient in building and optimizing large-scale, cloud-native data architectures integrating AI/ML model deployments.
Comfortable working in collaborative, cross-functional agile teams involving data engineering, analytics, and AI/ML functions.