Lead the design and development of Azure-based big data solutions, including batch and real-time ETL/ELT pipelines, data architecture, ingestion, curation, warehousing, and storage. Build solutions using Azure Data Factory, Databricks, Synapse, Spark, Python, SQL, and related Azure services. Support Salesforce migration and integration while applying strong RDBMS, data management, and big data design expertise.
Expertise on Azure platforms including Azure Databricks, ADLS, and its various components, • In-dept knowledge and hands-on experience in Microsoft Azure data stack i.e., Azure Data Factory, Azure SQL Database, Azure Functions, Logic apps, Spark and Python programming etc. • Expertise on Azure platforms including Azure Databricks and its various components, including Delta Lake. • Strong understanding of data architecture and data management principles. • In-dept knowledge and hands-on experience in Microsoft Azure data stack i.e., Azure Data Factory, Azure Synapse, Azure SQL Database, Azure Functions, Logic apps, Spark Knowledge etc. • In-depth Knowledge on designing of ETL Piplines for Batch and Real time in Azure data factory and Azure datafactory • Hands on experience on Function apps , Event Hubs,, Web apps , API M. • Good have to experience on Migration to Salesforce • Strong experience with designing ETL/ELT Pipelines/Data flows using Azure Data Factory as Primary skill and SSIS/Informatica as additional skills. • Proficiency in programming languages such as Python, SQL, Spark notebooks and Scala. • Must have strong development & design skills in leading RDBMS environments e.g. MS SQL Server and Oracle 10g. • Experience of Big data approach, architectural concepts, data sourcing/ ingestion/ curation and storage mechanisms. • Experience with real-time / near-real-time Data warehousing concepts and Design approaches.
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Design, build, and optimize end-to-end ETL/ELT pipelines using Python and PySpark for large structured and unstructured datasets. Ensure data quality through validation and reconciliation, troubleshoot performance issues, implement CI/CD and code review practices, and collaborate with IT and business stakeholders to translate requirements into scalable data solutions.
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AWSAzureBitbucketCi/CdData WarehousingDistributed ComputingEtl/EltGCPGitHadoopMicrosoft Sql ServerPysparkPythonSparkSQL
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