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PwC brand, Bangalore metro location, and mid-level generalist data role drive high competition.
Specialized cloud data engineering skills are transferable across industries but require Azure/Databricks experience.
Explicit 4–8 years plus mandatory Azure, Databricks, Hadoop, Spark and SQL requirements increase shortlisting strictness.
Lead end-to-end design and implementation of Cloud data engineering solutions using Azure technologies including Databricks, Data Factory, Synapse, and ADLS.
Develop, enhance, and optimize data processing workflows and pipelines, ensuring data governance and security adherence.
Mentor junior data engineers and collaborate with cross-functional teams to deliver analytics projects and actionable data insights.
4+ years of hands-on experience in Azure data engineering with expertise in ADLS, Data Bricks, Data Flows, HDInsight, Azure Analysis Services, Hadoop, and Spark.
Proficient in SQL (joins, groups, functions, stored procedures), data extraction from diverse sources (flat files, XML, JSON, Parquet, RDBMS), and Unix shell scripting.
Bachelor's degree in Engineering (BE/B.Tech), MCA, M.Sc, M.E, M.Tech, or MBA required.
Experience with Cloud data migration processes, DevOps tools (Git, CI/CD frameworks, Jenkins or GitLab), and creating design documents, test plans, and project documentation.
Experienced Azure data engineer capable of leading cloud development in agile teams with strong planning and organization skills.
Deep understanding of data management concepts, data modeling, data warehouse lifecycle, and big data frameworks.
Strong focus on technical expertise in Azure cloud solutions combined with mentoring abilities and adherence to quality and governance standards.