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Tier-1 employer, metro location, mid-level data role with broad Databricks/Hadoop requirements.
Specialized data platform skills are transferable but require tooling expertise, making cross-industry fit medium.
Explicit 5+ years and mandatory Databricks/Hadoop/Scala/Azure skills make filters stringent.
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Design, implement, and maintain a secure, scalable data infrastructure across AWS/Azure and data centers, focusing on data lakes, warehouses, stream processing, and unified query engines.
Own SLA compliance and monitor system-centric KPIs to meet or exceed expectations for availability, throughput, data consistency, security, and privacy.
Mentor engineers and drive software engineering best practices including monitoring, auditing, reliability, and security in data analytics tooling development.
At least 5 years of hands-on experience with Databricks on Azure Cloud.
Minimum 5 years of hands-on expertise in Hadoop and Scala.
Proficiency in at least one programming language: Python, Scala, or SQL.
Mandatory knowledge of at least one public cloud platform: AWS or Azure.
Experienced in end-to-end data engineering workflows and DevOps/DataOps practices in cloud environments.
Demonstrates strong ownership and prioritization skills to manage multiple data platform demands and SLA requirements.
Ability to operate in a dynamic, collaborative environment to scale data systems for varied business needs with mentoring capabilities.