Databricks Developer – Azure Cloud Data Engineer

About the role

The Cloud Data Engineer (Azure Databricks) will build, test, and maintain data pipelines on Azure Databricks to deliver reliable, high‑quality data for clinical, operational, and analytical teams. Working under senior data engineering leadership, the role contributes to the Enterprise Data Warehouse design with a focus on ingestion, transformation, and Lakehouse development.

Key responsibilities

• Design, develop, and support ETL/ELT pipelines using PySpark, Spark SQL, and Databricks notebooks for batch and streaming workloads.
• Implement Delta Lake best practices, including schema evolution, time‑travel, and performance optimization (OPTIMIZE, Z‑ORDER, VACUUM).
• Orchestrate workflows with Databricks Jobs and Azure Data Factory, integrating data from databases, SFTP, files, and REST APIs.
• Apply Medallion architecture (bronze/silver/gold) to create curated datasets for downstream analytics.
• Collaborate with business and clinical stakeholders to translate requirements into robust data solutions while ensuring compliance with HIPAA and GDPR.

Required profile

• 2–4 years of experience building cloud data engineering solutions on Azure, preferably in a healthcare context.
• Strong communication skills and ability to work effectively with both technical and non‑technical teams.
• Proven ability to manage task timelines, prioritize work, and adapt to changing requirements.
• Willingness to receive mentorship and eventually guide junior team members.

Required skills

• Azure Databricks
• PySpark
• Spark SQL
• Databricks notebooks
• Delta Lake
• Databricks Workflows / Jobs
• Azure Data Factory
• Medallion architecture
• Unity Catalog
• SQL (Azure SQL Database, Azure Synapse Analytics, Databricks SQL)
• Azure Data Lake Storage Gen2 & Azure Blob Storage
• Data modeling (conceptual, logical, physical)
• CI/CD practices (Git)

What we offer

• Salary: 1,800,000–2,400,000 NPR per year
• Working hours: 10:00 PM–6:00 AM onsite in Kathmandu