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About the role
Role & responsibilities Responsibilities - Contribute to data profiling initiatives across core RevOps and go-to-market (GTM) systems to evaluate data quality, consistency, and completeness. - Construct, deploy, and maintain scalable data workflows spanning Salesforce, Siebel CRM, Oracle ERP, SQL Server, and Azure Cloud data sources. - Engineer, support, and enhance robust data pipelines and automated transformation processes using SQL and big data technologies (e.g., Python, Hadoop, Spark). - Develop and implement database scripts, triggers, functions, and stored procedures. - Develop automated testing and validation procedures to enhance data quality management and compliance with data governance policies. - Participate with cross-functional teams across the organization to understand data needs within stakeholder contexts and how technical decisions impact analytics and reporting needs. - Work collaboratively with technical teams, operations, product managers, and business stakeholders to ensure alignment and effective implementation of data initiatives. - Identify and communicate data quality improvement process automation opportunities. - Actively contribute and promote a culture of engineering excellence. Required Skills & Qualifications - Extensive, hands-on experience working with Salesforce, Siebel CRM, and Oracle ERP. - Familiarity with marketing and sales automation platforms such as Demandbase, SalesLoft, and HubSpot. - Demonstrated proficiency in SQL and experience with large-scale data processing frameworks like Hadoop and Spark. - Experience working with BI/analytics tools, especially Power BI. - Experience with AI-powered database optimization tools. - Experience preparing data sets for use in machine learning and AI applications. - Excellent communication skills, with the ability to present findings and insights to both technical and non-technical audiences in a explicit and engaging manner. - Ability to thrive in a fast-paced, .
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