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Mid-level (4-6 yrs), known Tier-2 employer, and general software title with common skills increases competition.
High domain bias due to Databricks and AWS data engineering requirements.
Explicit 4-6 years and mandatory Databricks/AWS/Python stack make filters strict.
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Design, develop, and maintain scalable backend services with Python including building RESTful APIs for data integration and platform services.
Develop and manage data pipelines and workloads using Databricks, ensuring multi-tenant configurations with data isolation and performance.
Implement and monitor observability solutions (dashboards, metrics, logging) and proactively address system performance, reliability, and availability issues.
4-6 years of experience with Python and AWS Cloud engineering.
Strong hands-on experience with AWS services (e.g. Lambda, EC2, S3, IAM, CloudWatch).
Proven experience with REST API development and Databricks (Spark, notebooks, jobs, clusters).
Experience with multi-tenant architectures, system integration between big data platforms, and observability tooling.
Experienced in building and supporting distributed systems and data processing frameworks, especially in cloud-native environments.
Capable of collaborating effectively with cross-functional teams including data engineering, platform, and cloud operations.
Demonstrates expertise in security, performance, and cost optimization on AWS with a focus on scalable backend services.