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Tier-1 brand, mid-level generalist data role in metro with broad skillset increases applicant competition.
Core data engineering and analytics skills are broadly transferable across industries.
Mandatory 5+ years plus specific Azure, SQL, Databricks, and streaming skills make filtering stringent.
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Manage end-to-end data lifecycle including acquisition, preparation, and architecture to support analytics and AI/ML initiatives.
Develop and automate data analysis using SQL and Python to deliver business insights.
Collaborate with engineering, data science, and business teams to implement scalable data solutions using modern platforms (Azure, Spark, Databricks, Hadoop, Kafka).
Minimum 5 years of experience as a Data Analyst or in a similar data role.
Proficiency in SQL and Python for data analysis and automation.
Hands-on experience with Azure services including deployment automation using PowerShell/Azure CLI.
Familiarity with modern data platforms and tools such as Spark, Databricks, Hadoop, Kafka, and containerization technologies (Docker, Kubernetes).
Has strong technical expertise across the full data pipeline and data engineering principles supporting AI/ML projects.
Experienced working in Agile environments and cross-functional teams involving engineering and data science.
Capable of translating complex technical data insights into actionable business outcomes for stakeholders.