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Mid-level metro Data Engineer at a known fintech with broad Azure/Snowflake requirements, making it highly competitive.
Requires specific Azure, Snowflake, SSIS ETL expertise, so cross-industry transferability is limited.
Mandatory Azure, Snowflake, SSIS and 4+ years data engineering experience indicate high shortlisting strictness.
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Design, develop, and maintain enterprise data integration and warehousing solutions using Azure Data Factory, Snowflake, SQL Server, and SSIS.
Build and support scalable ETL/ELT pipelines along with operational, analytical, and executive reporting solutions using SSRS and optimize database performance.
Implement CI/CD pipelines for automated deployment, monitor data pipelines, troubleshoot production issues, and ensure data quality, governance, and compliance.
Minimum 4+ years of experience in Data Engineering, Data Warehousing, and Reporting solutions.
Education: BE/BTech/MCA/MTech/BSc in Computer Science, IT, or related field.
Strong hands-on experience with Azure Data Factory, Azure SQL, Event Hub, Snowflake Data Warehouse, Microsoft SQL Server, SSIS, and SSRS.
Experience working in Agile/Scrum environments and with globally distributed teams across multiple time zones.
Experienced in cloud-based data engineering with expertise in Azure and Snowflake technologies, capable of handling enterprise-scale data solutions.
Familiar with DevOps practices including CI/CD pipeline implementation and automated deployment using GitLab and Harness.
Strong analytical and troubleshooting skills with the ability to collaborate with business stakeholders and global technical teams to deliver scalable, compliant data platforms.