SQL Business Analyst 

Meritore Technologies is hiring a SQL Business Analyst for a contract position supporting data exploration and monitoring initiatives. The role focuses on analyzing newly acquired datasets, identifying trends and anomalies, generating business insights, and coordinating with client teams to access and interpret data.

Responsibilities:

• Performing analysis on newly acquired datasets using existing tools, dashboards, and curated datasets prepared by in house COVE data analysts
• Identifying early trends, anomalies, or potential signals within the data
• Applying business logic and contextual understanding to interpret data behavior and surface meaningful insights
• Helping create initial “views” into the data that can be used for - issue analysis, trend tracking, early monitoring outputs
• Explore datasets to understand how the data reflects business workflows and operational behavior. This may require basic knowledge of SQL and Excel to extract and manipulate data to find trends
• Identify patterns, inconsistencies, or gaps in the data from a business and experience perspective
• Demonstrate how the data can be used to answer business questions and support monitoring at COVE
• Identify and gain access to relevant datasets
• Navigate data access challenges across organizational boundaries
• Act as a liaison to help COVE understand - - what data is available - how it is structured - what limitations exist - how it can be used while maintaining governance and quality

Requirements:

• Working knowledge of SQL and/or data tools sufficient to explore datasets and validate outputs where needed
• Ability to use tools such as Power BI, Excel, or curated dashboards to analyze and interpret data
• Ability to quickly understand - data structure, key fields and relationships, basic data limitations
• Strong ability to work across organizational boundaries and collaborate with diverse stakeholders
• Strong communication skills to explain insights clearly translate data outputs into business context and bridge conversations between technical and non-technical teams
• Comfort operating in ambiguous environments where - ownership may not be clearly defined and datasets and requirements may evolve
• Ability to build relationships with data owners analysts and operational stakeholders
• Strong analytical thinking focused on identifying patterns, interpreting trends and surfacing meaningful insights
• Ability to use business logic and context to interpret data rather than relying solely on technical outputs
• Ability to connect data behavior to real-world operational impact
• Comfort working in exploratory environments where there is no predefined analysis framework and the goal is to understand and derive value from new datasets
• Ability to prioritize what is meaningful vs noise and what insights require escalation vs observation