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Mid-level metro Data Engineer role with common title and broad applicant pool despite Azure specialization.
Azure Databricks and cloud infra focus favors candidates with specific Azure data-platform background.
Multiple mandatory Azure Databricks, Synapse, Spark, and CI/CD/IaC requirements enforce strict filtering.
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Lead design and architecture of large-scale data infrastructure and pipelines on Azure Databricks (Data Lakehouse).
Develop automated, secure data ETL/ELT solutions in Azure, optimizing for storage and compute costs.
Troubleshoot production pipeline failures, ensure data quality, and drive governance, security, and reliability best practices.
5–8 years of experience in data engineering or platform roles (8+ years often preferred).
Expert hands-on skills in Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Strong proficiency in SQL (OLAP, OLTP, dimensional modeling) and Python/Scala for Spark.
Experience with CI/CD, Infrastructure as Code (IaC), and knowledge of data security/compliance (RBAC, encryption, GDPR).
Experienced in designing and managing scalable Azure cloud data architectures focusing on cost optimization and security.
Proficient in integrating complex business requirements into robust, automated data pipelines with proven troubleshooting capabilities.
Able to mentor and coordinate effectively with global cross-functional teams including data scientists and analysts.