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Mid-level popular Python/Databricks data-engineer role with broad skillset at a well-known mid-tier employer.
Skills like Python, Databricks, and AWS are highly transferable across industries.
Explicit 4–6 years plus mandatory Databricks, AWS, and backend data engineering skills make filters strict.
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Design, develop, and maintain scalable backend services and RESTful APIs primarily using Python and Flask.
Develop and manage data pipelines and workloads on Databricks, ensuring multi-tenant data isolation and performance.
Implement observability solutions and monitor system health to maintain performance, reliability, and availability on AWS cloud environment.
4-6 years of professional experience in Python development and AWS Cloud engineering.
Strong hands-on experience with Python, AWS services (Lambda, S3, API Gateway, EC2, IAM, CloudWatch), and Databricks (Spark, notebooks, jobs, clusters).
Proven experience in building and consuming REST APIs and multi-tenant architecture design.
Experience with system integration between big data platforms, observability tools (monitoring, dashboards, logging), and distributed data processing frameworks.
Experienced in backend and data engineering with deep knowledge of AWS cloud-native services and Databricks environment.
Capable of managing scalable, multi-tenant backend services and data pipelines with strong emphasis on performance and security.
Familiar with cross-functional collaboration between data engineering, platform, and cloud operations teams in cloud infrastructure projects.