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Strong employer brand, metro location, popular mid-level data role, and broad skill requirements increase competition.
Data engineering skills (Azure, Spark, ETL, SQL) are highly transferable across industries.
Explicit 4+ years plus mandatory Azure/Databricks, Hadoop, Spark, SQL and DevOps skills make filters strict.
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Design and develop Azure Databricks-based data solutions and data pipelines to support client analytics needs.
Collaborate with cross-functional teams and mentor junior data engineers, ensuring adherence to data governance and quality standards.
Analyze complex data problems and improve data processing workflows for enhanced efficiency and actionable insights.
4+ years of professional experience in Azure data engineering, including ADLS, Databricks, HDInsight, and Azure Analysis Services.
Mandatory experience with Big Data frameworks, specifically Hadoop and Spark, and strong SQL skills including stored procedures.
Bachelor's degree in Engineering, MCA, M.Sc, M.E, M.Tech, or MBA is required.
Proficiency in English communication (oral and written) is mandatory.
Experienced in cloud data engineering with a focus on Azure and Big Data technologies, capable of leading complex projects and mentoring peers.
Strong understanding of data management concepts, data modeling, and data warehouse lifecycle documentation.
Familiar with application DevOps tools (Git, CI/CD frameworks, Jenkins, GitLab) and capable of managing source code and deployment processes.