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Mid-level, metro-based cloud data role with common skills and generalist title, high applicant competition.
Cloud data engineering skills are broadly transferable across industries.
Explicit 3-5 years and mandatory Databricks/Azure/AWS/Spark/Python skills create strict filtering.
Build, support, and maintain scalable cloud-based data solutions across Azure and AWS using Databricks, Spark, Python, and SQL.
Develop and operate data ingestion and transformation pipelines including API-based data ingestion from multiple platforms.
Collaborate with cross-functional teams to ensure secure, reliable, cost-effective data delivery for reporting, analytics, AI, and operational decisions.
Bachelor's degree in Computer Science, IT, Data Engineering, or related field (or equivalent experience).
3-5+ years of experience in cloud engineering, data engineering, systems integration, or related technical roles.
Hands-on experience with Databricks, Spark, SQL, Python, REST APIs, and cloud-native solutions on Microsoft Azure and AWS.
English proficiency in written and spoken communication with technical and business stakeholders.
Experienced in working within matrixed, cross-functional environments involving FinOps, security, analytics, and architecture teams.
Skilled in cloud services (Azure and AWS) and data integration automation, with exposure to infrastructure as code (Terraform, ARM templates) and cloud monitoring.
Demonstrates ownership and accountability for resolving data and integration platform issues, aligning engineering practices with governance and cost-efficiency.