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Senior Data AnalystRole: Senior Data Analyst Location: Deerfield Beach FL (Hybrid - 3 Days a week onsite) Contract: 6+ Months Contract Must take initiative, not be a task master, must be a critical thinker, understand business outcomes, keep up with demands, must be a go getter, great communication, great dialogue with the business, think outside the box. Key Skills: Manager Took over data and BI engineering Data analysts and data governance Teams that support sales finance operation customer service and claims Demanding priorities Must be very Analytical Data solutions analyst Data engineering and analysts Not building pipelines Must write SQL that will be utilized by a data engineer Heavier critical thinking Solutions skills Power BI nice to have Met with stakeholders and business users AI understanding of how copilot can be utilized in day to day work How to structure query so it's built to right technology Moving to fabricJob Summary The Senior Data Analyst plays a key role in transforming data into actionable insights and scalable solutions that support business growth and strategic decision-making. This position partners closely with business stakeholders, technology teams, and data engineers to understand business needs, design and support data solutions, ensure data quality and governance, and deliver meaningful analytics that drive results. The ideal candidate combines strong analytical and technical skills with business acumen, thrives in a collaborative environment, and is passionate about using data, modern analytics platforms, and emerging technologies to solve complex business challenges and create value across the organization.Key Responsibilities Data Analysis, Quality, Testing & Operational Excellence Analyze business data to support management, project teams, data product teams, business stakeholders, and senior leadership. Present findings, recommendations, and project updates to stakeholders at all levels of the organization. Develop, execute, and optimize SQL queries to retrieve, profile, aggregate, validate, and analyze data across multiple systems. Support the full data lifecycle by ensuring data solutions are properly tested, validated, and aligned with change management processes before and after production deployments. Perform data profiling, quality assessments, validation, testing, and business rule analysis to ensure data accuracy, completeness, consistency, and alignment with business requirements. Identify and coordinate test data and testing activities to validate data mappings, transformations, semantic models, reporting outputs, and downstream data solutions. Research, diagnose, and resolve data issues, reporting inconsistencies, data gaps, and process anomalies through root cause analysis and continuous improvement efforts. Business Partnership & Solution Delivery Collaborate with business stakeholders, management, ITS, and data engineering teams to gather requirements, validate business definitions, identify data solution opportunities, and prioritize business and information needs. Translate business processes, questions, and stakeholder needs into data, reporting, semantic modeling, and advanced analytics requirements, including opportunities where AI-enabled tools may improve efficiency or insight. Maintain a strong understanding of business systems, operational data, reporting capabilities, business priorities, and the broader JM Family data ecosystem. Partner proactively with technology and business teams to strengthen alignment between data, systems, and business processes while anticipating downstream impacts. Data Architecture, Modeling & Engineering Partnership Work within modern cloud data warehousing environments and apply concepts including dimensional modeling, star schemas, semantic data models and ETL/ELT processes used to support data warehouse and analytic solutions. Perform data lineage analysis, validate SQL transformations and business logic, and troubleshoot issues across data processing pipelines. Partner closely with data engineers to support the design, delivery, maintenance, and ongoing improvement of enterprise data solutions. Create, maintain and oversee source-to-target mappings and ensure alignment between business requirements, data transformations, and downstream systems. Data Governance, Documentation & Continuous Improvement Create and maintain data documentation, including data models, data dictionaries, entity-relationship diagrams, technical specifications, mapping documentation, analysis results, and governance-related artifacts. Execute and promote data management, data governance, information security, and related standards, policies, and best practices. Participate in data governance activities and provide subject matter expertise on data usage, data flows, reporting, systems, business processes, and technology initiatives. Support operational activities, strategic initiatives, project delivery, and continuous improvement efforts, including identifying opportunities to leverage AI technologies to enhance data analysis processes. Apply project management principles to support planning, prioritization, execution, and communication of assigned work.Required Qualifications Bachelor's degree in a related field or equivalent work experience. 5+ years of experience in data analytics, business intelligence, data solutions, or business analysis. Advanced SQL experience and strong data analysis skills. Experience with data warehousing concepts, dimensional modeling, and semantic data models. Experience validating, troubleshooting, and analyzing data across multiple systems. Experience partnering with data engineering or technology teams to support data solution delivery, validation, and issue resolution. Strong critical thinking, documentation, communication, and stakeholder management skills.Preferred Qualifications Experience with cloud-based data platforms and modern data architecture. Experience with Power BI or other enterprise business intelligence tools for data visualization. Experience with data governance and metadata management practices. Experience leveraging AI-enabled tools to improve analytics, documentation, data preparation, or other repeatable data management processes. Ability to translate business questions and stakeholder needs into a data model. Create KPIs, perform trend analysis, and provide actionable insights and recommendations that support business decision-making.