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Tier-1 employer plus mid-level generalist role and popular Databricks/Airflow/Snowflake stack.
Core data engineering skills transferable, but healthcare platform context raises moderate domain specificity.
Explicit 4+ years plus mandatory Databricks, Airflow, Snowflake, Azure, and Python requirements.
Design, develop, and maintain scalable data pipelines using Databricks (Spark/PySpark), orchestrate workflows with Apache Airflow, and optimize ELT pipelines in Snowflake.
Develop and deploy production-quality Python code and APIs using modern frameworks and Azure-native services, ensuring cloud best practices for security, scalability, and cost optimization.
Troubleshoot complex production issues, participate in architecture design and technical decision-making, and collaborate with cross-functional teams to support downstream data consumption.
Bachelor's degree in B.Tech, MCA, or Graduation.
Minimum 4 years of total professional experience.
Hands-on experience with Databricks (Spark/PySpark), Apache Airflow, Snowflake, Python programming, and Microsoft Azure cloud services.
Experience building and hosting REST APIs with Python frameworks; familiarity with Azure Functions, App Services, and API Management.
Experienced in end-to-end design and independent delivery of complex data engineering solutions in cloud-native environments (Azure).
Strong operational exposure to data warehousing, ELT pipeline development, workflow orchestration, and performance tuning within Snowflake and Databricks ecosystems.
Technically skilled in Python API development, CI/CD best practices, and managing production data pipelines with observability and reliability focus.