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Tier-1 employer plus a mid-level generalist Azure/Databricks data engineer role drives high competition.
Core Azure/Databricks data engineering skills are broadly transferable across industries, so sensitivity is low.
Explicit 2–6 years plus required Azure Data Factory, Databricks, CI/CD and production experience implies high strictness.
Own and ensure stability, scalability, and performance of cloud-based data pipelines, focusing on batch processing.
Monitor, maintain, and optimize Databricks workloads and cloud infrastructure for cost efficiency.
Improve operational processes including incident handling, performance monitoring, and issue resolution in a cloud data environment.
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field.
2 to 6 years work experience in operating and maintaining large-scale cloud data solutions, specifically in Azure Data Factory and Databricks.
Hands-on experience with Azure Data Factory, Databricks, Lakehouse architecture, batch accounts, IAC, GitHub, IAM, CI/CD pipelines, and command-line scripting (e.g., PowerShell).
Experience with monitoring and logging tools is a plus; experience in automotive domain is also a plus but not mandatory.
Proven expertise in managing and optimizing cloud-based data engineering solutions with a focus on Azure and Databricks.
Experience operating production environments to ensure performance and cost optimization.
Comfortable working within structured DevOps environments using CI/CD, GitHub, and infrastructure-as-code tools.