Data Engineer - Data Modernization

We are seeking a hands-on Data Engineer to support a major data modernization initiative as the organization transitions its legacy data warehouse and integration ecosystem to a modern cloud-based architecture built on Snowflake, dbt, Microsoft Fabric, Apache Airflow, and IBM StreamSets.

• 5+ years of experience in Data Engineering, Data Warehousing, or Data Integration. \n

• Strong hands-on experience with Snowflake. \n

• Strong hands-on experience with dbt. \n

• Advanced SQL and relational database expertise. \n

• Experience building and maintaining enterprise-scale data pipelines and integrations. \n

• Experience working on data warehouse modernization or migration initiatives. \n

• Strong analytical thinking and problem-solving skills. \n

• Ability to work independently with minimal supervision. \n

• Demonstrated ability to quickly learn and implement new technologies. \n

• Experience leveraging AI-assisted development tools in a professional environment with measurable productivity gains. \n

• Strong communication and stakeholder management skills. \n

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field. \n, * Hands-on experience with Apache Airflow. \n

• Experience with IBM StreamSets. \n

• Experience working with Microsoft Fabric. \n

• CI/CD implementation experience within data engineering environments., We’re looking for someone who enjoys working with modern technologies, stays current with industry trends, and knows how to apply them to solve real business challenges. The ideal candidate combines strong technical expertise with practical problem-solving skills and can quickly understand complex environments while contributing immediately.

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• Design, develop, and support scalable data engineering solutions within Snowflake. \n

• Build, optimize, and maintain data transformation models and workflows using dbt. \n

• Support migration from SQL Server and legacy data warehouse platforms into Snowflake. \n

• Develop and maintain enterprise-grade data pipelines, data integrations, and data feeds. \n

• Leverage IBM StreamSets to support data migration, integration, and enterprise data movement processes. \n

• Implement orchestration and scheduling workflows using Apache Airflow and/or Microsoft Fabric. \n

• Modernize and enhance legacy ETL processes, including those built on SAP Data Services. \n

• Implement and improve CI/CD practices across data engineering environments. \n

• Utilize AI-assisted engineering tools for development, troubleshooting, testing, documentation, and productivity improvements. \n

• Identify and automate manual operational and engineering processes. \n

• Collaborate closely with internal stakeholders, engineering teams, and implementation partners throughout the modernization journey. \n

• Troubleshoot and resolve data integration, transformation, orchestration, and performance issues. \n

• Contribute to engineering standards, best practices, governance, and framework development. \n

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\n, * Experience migrating data from SQL Server or other traditional RDBMS platforms to Snowflake. \n

• Experience orchestrating dbt, StreamSets, and cloud-native data workflows. \n

• Experience modernizing legacy ETL and data integration platforms. \n

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Good to Have

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• Python development experience. \n

• Azure Data Services and Azure Storage experience. \n

• SAP Data Services experience. \n

• Experience working with managed service providers or consulting partners during technology transformations. \n

• Experience introducing modern engineering tools, frameworks, or best practices within enterprise environments. \n

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WHY YOU’LL LIKE IT HERE

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• Opportunity to work on a large-scale enterprise data modernization initiative. \n

• Exposure to modern data technologies including Snowflake, dbt, Microsoft Fabric, Airflow, and StreamSets. \n

• Collaborative environment focused on innovation, automation, and AI-driven engineering practices. \n

• Continuous learning and growth opportunities within a global technology organization. \n

• Ability to make a significant impact on the future state of the organization’s data platform. \n

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Incedo is a global AI, data, and digital transformation specialist that helps leading enterprises drive innovation and business growth through technology. With over 4,000 professionals across the US, Canada, Latin America, and India, Incedo combines expertise in AI, data analytics, and digital engineering to deliver impactful solutions across Banking & Payments, Telecom, Hi-Tech, Wealth Management, and Life Sciences. At Incedo, we foster a culture of innovation, collaboration, and continuous learning, empowering our people to solve complex challenges and shape the future of technology.