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Tier-1 brand, metro location, and a popular mid-level data engineering profile increase candidate competition.
Data engineering skills transfer across industries, but Azure/Databricks consulting experience creates moderate domain specificity.
Explicit 6+ years requirement plus mandatory Azure Databricks, Python, SQL, and Spark skills makes shortlisting strict.
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Design, develop, and manage scalable, secure data pipelines on Azure using Databricks and Azure Data Factory.
Write reusable Python code for cloud automation, data processing, and orchestration; optimize ETL workflows and troubleshoot performance bottlenecks.
Architect and implement cloud-native data solutions integrating structured/unstructured data; lead code reviews and contribute to enterprise data warehousing deployments.
6+ years overall experience in cloud or data engineering; 2-3+ years hands-on experience with Azure cloud services.
Strong Python programming skills, including advanced scripting and cloud SDK experience (Must-Have).
Strong SQL skills and hands-on experience with Azure Databricks (Must-Have).
Bachelor’s degree required (BE/B.Tech/MBA/MCA); Master of Business Administration also noted.
Experience building scalable ETL pipelines and integrating BI tools in cloud environments, particularly Azure.
Proficient in data modeling (normalization/denormalization), Apache Spark, and Azure storage solutions like Data Lake and Blob Storage.
Familiar with version control (Git), code reviews, and maintaining performance in complex data workflows; operates well in advisory or consulting contexts.