Job Summary We are seeking an experienced Senior Data Engineer with strong expertise in Snowflake Python Azure Cloud Spark SQL and Kubernetes to design develop and maintain scalable data platforms and analytics solutions. The ideal candidate will have hands-on experience in cloud-native data engineering data pipeline orchestration CI/CD automation and AI/ML model deployments. Experience with Databricks and the Healthcare domain will be highly preferred. Key Responsibilities Design develop and optimize scalable ETL/ELT data pipelines using Snowflake Python and Apache Spark. Build and maintain cloud-based data platforms on Microsoft Azure. Develop and manage data ingestion transformation and loading processes for structured and semi-structured datasets. Implement and optimize data warehouse solutions in Snowflake for high-performance analytics. Orchestrate workflows using Apache Airflow for reliable and automated data processing. Deploy and manage containerized applications using Kubernetes. Build CI/CD pipelines using GitHub Actions to automate code deployment and infrastructure changes. Collaborate with Data Scientists to deploy monitor and maintain AI/ML models in production environments. Implement best practices for data quality governance security and performance optimization. Create scalable analytics datasets to support business intelligence and reporting. Troubleshoot production issues and optimize system performance across cloud environments. Work closely with cross-functional teams including Data Science Business Intelligence Product and Engineering. Ensure compliance with Healthcare data standards security and privacy regulations where applicable. Required Technical Skills Snowflake Python SQL Apache Spark Microsoft Azure Kubernetes GitHub (CI/CD & GitHub Actions) Apache Airflow Data Analytics AI/ML Model Deployment REST APIs Data Warehousing Concepts ETL/ELT Pipeline Development Version Control (Git) Preferred Skills Databricks Delta Lake Azure Data Factory (ADF) Azure Data Lake Storage (ADLS Gen2) MLflow Docker Terraform Azure DevOps Healthcare domain experience (HIPAA/FHIR/HL7 knowledge is an added advantage) Qualifications Bachelor's or Master's degree in Computer Science Information Technology Data Engineering or a related field. 5–8 years of experience in Data Engineering Cloud Data Platforms or Analytics Engineering. Strong problem-solving analytical and debugging skills. Excellent communication and stakeholder management abilities. Experience working in Agile/Scrum environments. Preferred Experience Hands-on experience building enterprise-scale data platforms. Experience deploying machine learning models into production. Exposure to healthcare data ecosystems and regulatory compliance. Experience with large-scale data processing and cloud-native architectures. Work Location Remote