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Mid-level popular backend role with broad cloud and Databricks requirements increases competition.
Strong cloud, Databricks, and backend data engineering bias limits transferability across industries.
Explicit 4–6 years plus mandatory Python, AWS, Databricks, and multi-tenant expertise creates high filtering.
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Design, develop, and maintain scalable backend services and RESTful APIs using Python and AWS Cloud services.
Develop and manage data pipelines and multi-tenant configurations on Databricks, ensuring data isolation and performance.
Implement and manage observability solutions to monitor system health, performance, reliability, and availability, collaborating with cross-functional teams.
4-6 years of relevant work experience in Python backend development and AWS Cloud engineering.
Strong hands-on experience with Python, AWS services including Lambda, S3, API Gateway, EC2, IAM, CloudWatch.
Proven expertise in REST API development and consumption.
Hands-on experience with Databricks including Spark, notebooks, jobs, clusters, and familiarity with multi-tenant architectures and observability tools.
Experienced in integrating big data platforms, especially between Databricks and systems like HBase.
Skilled in designing distributed systems and data processing frameworks in cloud-native environments.
Demonstrates operational ownership in monitoring and optimizing cloud backend services for security, cost, and performance.