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Tier-1 employer, mid-level data engineer role, metro location and common skillset increase applicant competition.
Azure, Spark and SQL skills are broadly transferable across industries but require specific cloud/big-data expertise.
Explicit 4+ years plus mandatory Azure/Databricks/Hadoop/Spark and SQL requirements enforce strict technical filters.
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Design and develop end-to-end data solutions using Azure Databricks and related Azure data services.
Lead data pipeline development and enhancements focusing on data processing efficiency and analytics project delivery.
Mentor junior data engineers and ensure adherence to data governance, security, and quality standards.
4+ years of experience with Azure ADLS, Databricks, HDInsight, Azure Analysis Services, Hadoop, and Spark.
Proficiency in SQL including joins, groups, functions, and stored procedures; experience with data extraction from diverse sources like flat files, XML, JSON, Parquet, and RDBMS.
Bachelor’s degree in Engineering, MCA, M.Sc, M.E, M.Tech, or MBA.
Experience with Unix Shell Scripting and DevOps tools such as Git, Jenkins, CI/CD frameworks.
Experienced in cloud data engineering, especially Azure cloud solutions and Big Data frameworks like Hadoop and Spark.
Skilled in planning and organizing data engineering efforts within agile, collaborative teams.
Certifications in Azure or Databricks and demonstrated ability to lead cloud-based development projects.