Employer description & source details
Relevant experience in data engineering, data integration, business intelligence, or application support. Expert-level proficiency in Power BI, including dashboard development, DAX calculations, data modeling, refresh management, and troubleshooting. Strong hands-on expertise in Snowflake, including SQL query optimization, views, and stored business logic. Hands-on experience with SnapLogic and MuleSoft, including Mule 4 and DataWeave, with strong proficiency in at least one and working knowledge of the other. Practical experience with Salesforce Data Cloud, including Data Lake Objects (DLOs), streaming and batch Data Transforms, and data integration. Strong understanding of data ingestion, transformation, integration, and reporting workflows. Ability to read, understand, and debug R scripts, with working knowledge of Python for data logic migration and validation. Experience troubleshooting data pipeline failures, data quality issues, dashboard refresh errors, and integration problems. Strong analytical, problem-solving, prioritization, and incident management skills. Excellent ownership, documentation, and stakeholder communication skills. Experience working in a multi-application support or shared-services environment is preferred. Exposure to data pipeline observability, monitoring, alerting, and operational support practices is preferred. Relevant certifications in Snowflake, MuleSoft, Salesforce Data Cloud, or Microsoft Power BI (PL-300) are desirable. Maintain and support the brokerage dashboard application, ensuring accurate and timely reporting to help brokers and market leaders improve pipeline accuracy and drive revenue growth. Ensure the reliability of the client intelligence platform, enabling teams to leverage a unified client view for stronger engagement,
Extracted skills: python, sql, power bi