Data Engineer

Key Responsibilities

• Keep the brokerage dashboard application accurate and timely, so brokers and market leaders can rely on it to improve pipeline accuracy and drive revenue growth.
• Keep the client intelligence platform reliable, so teams can use the unified client view to strengthen engagement, growth strategies, and revenue opportunities.
• Maintain, optimize, and debug Snowflake SQL queries, views, and stored business logic.
• Support, monitor, and update SnapLogic pipelines that move data from source systems into Snowflake.
• Maintain Power BI dashboards, update DAX calculations, and resolve refresh and reporting issues.
• Support R-based data integrity and validation scripts, and help migrate that logic to Snowflake and Python.
• Manage and troubleshoot Salesforce Data Cloud Data Lake Objects (DLOs) and streaming and batch Data Transforms.
• Maintain and update Mule 4 flows and DataWeave transformations for objects not natively supported in Data Cloud.
• Provide coverage across both applications, reducing single points of failure.
• Perform incident triage and root-cause analysis spanning ingestion, transformation, and reporting layers.
• Keep documentation, monitoring, and support runbooks consistent across both applications.

Required Qualifications

• 5+ years in data engineering, integration, or BI support.
• Strong SQL and Snowflake expertise.
• Hands-on experience with at least one of SnapLogic or MuleSoft (Mule 4 and DataWeave), and working proficiency in the other.
• Working knowledge of Power BI and DAX.
• Working experience with Salesforce Data Cloud.
• Ability to read and debug R, with Python for migration work.
• Strong ownership, prioritization, and stakeholder communication skills.

Preferred Qualifications

• Experience in a multi-application support or shared-services model.
• Relevant certifications (Snowflake, MuleSoft, Salesforce Data Cloud, Microsoft PL-300).
• Exposure to observability and alerting practices for data pipelines.