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Tier-1 brand and Mumbai metro increase candidate density despite specialized cloud-data skillset.
Core cloud data architecture skills transfer across industries, though domain experience is preferred.
Explicit 8–12 years plus mandatory Azure/Databricks certification and specific tech stack.
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Design and implement scalable big data architectures and ETL pipelines using PySpark, SparkSQL, Databricks, and Azure Data Factory on Azure or AWS.
Ensure data quality, security, governance, and compliance while managing metadata frameworks and version control with Git and DevOps.
Collaborate with cross-functional teams and leverage domain knowledge in banking, insurance, or pharma to deliver tailored data solutions and manage project timelines.
8-12 years of relevant work experience in big data and cloud data architecture.
Proficient in PySpark, SparkSQL, Databricks on Azure, Azure Data Lake Storage Gen2, Azure Data Factory, Azure Event Hub, and Synapse.
Must have certifications in Azure, Databricks, or related cloud technologies.
Bachelor's degree in Technology or Master of Business Administration (MBA).
Experienced in handling complex data architectures with strong technical expertise in Azure cloud ecosystem and DevSecOps practices.
Familiar with data governance, quality frameworks, and able to translate technical concepts to diverse stakeholders.
Industry experience in banking, insurance, or pharma preferred for tailoring data solutions effectively.