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Tier-1 brand, metro location, mid-level generalist data role with broad Azure/Spark requirements.
Azure Databricks and data engineering skills are broadly transferable across industries.
Explicit 4+ years and many mandatory Azure, Hadoop, Spark, SQL, and DevOps requirements.
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Lead end-to-end implementation of Cloud data engineering solutions using Azure Databricks and related Azure services.
Design, develop, and enhance data processing workflows ensuring efficiency and adherence to data governance and security protocols.
Mentor junior data engineers, collaborate with cross-functional teams, and support client analytics projects to derive actionable insights.
4+ years of hands-on experience with Azure ADLS, Databricks, HDInsight, Azure Data Factory, Azure Synapse, Hadoop, and Spark.
Bachelor’s degree in Engineering, MCA, M.Sc, M.E, M.Tech, or MBA.
Strong proficiency in SQL, data extraction from diverse sources (flat files, XML, JSON, Parquet, RDBMS), and Unix shell scripting.
Experience with Cloud data migration processes and DevOps tools (Git, CI/CD frameworks, Jenkins, GitLab).
Experienced in leading cloud data engineering delivery on agile teams with strong planning and organizational skills.
Familiarity with data management concepts, data modeling, and data warehouse lifecycle documentation.
Certified or skilled in Azure/Databricks certifications with practical knowledge of big data ML toolkits and streaming systems.