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Mid-level cloud/data role, metro location, broad stack, and popular title create high applicant competition.
Cloud data engineering skills (Databricks, Azure, AWS) are highly transferable across industries.
Multiple mandatory skills, certifications, and 5+ years experience make filtering strict.
Design, build, and support scalable cloud data platforms and ETL/ELT pipelines using Azure, AWS, Databricks, Spark, PySpark, SQL, and Python.
Develop and manage secure API ingestion and integration with internal, vendor, and enterprise data sources.
Promote automation, CI/CD, monitoring, infrastructure as code, and collaborate across teams to ensure secure, governed, cost-effective, enterprise-ready cloud data solutions.
Bachelor's degree in Computer Science, IT, Data Engineering, or related field (or equivalent experience).
5+ years experience in cloud engineering, data engineering, or systems integration roles.
Hands-on expertise with Databricks, Spark, PySpark, SQL, Python, Microsoft Azure, and AWS cloud services.
Experience with Azure DevOps, Terraform, CI/CD, automation, monitoring, and infrastructure as code.
Experienced in designing and enhancing complex data pipelines and lakehouse architectures at enterprise scale.
Able to lead technical mentoring, establish engineering standards, and work effectively in a matrix organization.
Certified in Databricks, Microsoft Azure, or AWS, with strong understanding of cloud security, governance, and FinOps principles.