Senior Associate - Data Engineering (Azure Synapse, ETL, Power BI, Azure Storage) Role Overview We are seeking a highly skilled and motivated Senior Associate - Data Engineering to join our growing analytics and data platform team. The ideal candidate will have deep expertise in designing and developing robust, scalable ETL pipelines using Azure Synapse Analytics and other modern Azure data services. You will play a key role in developing data pipelines, optimizing query performance, and transforming enterprise-scale datasets to power analytics, AI/ML, and business intelligence solutions. Key Responsibilities o Design and develop scalable ETL/ELT pipelines using Azure Synapse Analytics, Data Factory, and SQL-based transformations. o Implement and optimize Power BI dashboards including Power Query transformations, data modeling, and advanced DAX measures. o Ingest, store, and manage large datasets in Azure Data Lake Storage (Gen2), Blob Storage, and Azure SQL Database. o Collaborate with data scientists, analysts, and business teams to translate requirements into production-grade data pipelines and reporting solutions. o Manage data ingestion and transformation workflows from multiple sources (cloud, on-prem, APIs). o Apply strong understanding of data partitioning, security, lineage, and governance practices. o Build and maintain CI/CD pipelines for automated deployment of data workflows and Power BI assets using Azure DevOps. o Monitor, troubleshoot, and optimize pipeline performance and costs across Azure cloud services. o Preferred: Support or develop data services using Azure Service Fabric for scalable and resilient compute workloads. o Participate in peer reviews, mentoring sessions, and documentation for operational handoff. Required Skills & Experience o 6-8 years of hands-on experience in data engineering, especially within Azure-based environments. o Proficiency in Azure Synapse Analytics, Azure Data Factory, and Azure SQL. o Strong skills in Power BI development including DAX, Power Query, and data refresh scheduling. o Demonstrated experience working with Azure Storage services: o Azure Data Lake Storage Gen2 o Azure Blob Storage o Azure Files o Proficient in writing and optimizing T-SQL queries, transformations, and table design. o Familiar with dimensional modeling, data lakehouse architectures, and metadata management. o Experience with version control, release pipelines, and automation tools in a CI/CD setup. o Certfification in Azure Data Engineering (DP-203) is preferred. o Excellent problem-solving, collaboration, and communication skills."
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