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Moderate due to remote hiring and popular data-engineer title balanced by seniority and specialized Azure/Databricks skills.
High because role demands deep Azure Databricks, Spark, lakehouse and cloud platform expertise, limiting cross-industry portability.
High due to explicit 8+ years, mandatory Azure Databricks/Spark/Scala expertise and leadership requirements.
Lead design, development, deployment, and maintenance of enterprise-scale data and analytics platforms.
Build and optimize scalable, reliable ETL/ELT data pipelines and cloud data solutions primarily on Azure, ensuring data quality, governance, and compliance.
Provide technical leadership, mentor team members, and collaborate with multi-disciplinary stakeholders to deliver data engineering initiatives from concept through production.
8+ years of hands-on experience in Data Engineering, Data Platform Engineering, Big Data, or related domain.
3+ years experience leading technical teams or significant data engineering projects.
Bachelor’s degree or equivalent in Computer Science, IT, Engineering, Data Science, or relevant field.
Experience with Azure cloud data services (Databricks, ADLS, Synapse), Spark, Python/Scala, SQL, and CI/CD tools explicitly required.
Experienced in building large-scale cloud-based data ingestion and transformation platforms with strong operational delivery focus.
Demonstrates technical leadership balancing strategic architecture and hands-on execution in Azure and big data ecosystems.
Skilled in implementing data governance, quality frameworks, DevOps, and Agile methodologies aligned with enterprise compliance and regulatory requirements.