Role Description We are seeking a highly analytical and business-oriented Data Business Analyst with expertise in Business Intelligence, Data Analytics, Reporting, and Stakeholder Management. The ideal candidate will be responsible for transforming complex business data into actionable insights, supporting strategic decision-making, and driving operational efficiency through scalable data solutions. The candidate should have strong experience in data analysis, dashboard development, KPI reporting, and collaborating with cross-functional business and technology teams. Experience in Healthcare domain and multi-cloud analytics environments is highly preferred. Key Responsibilities - Gather, analyze, and document business requirements from stakeholders across multiple business functions. - Develop and maintain Business Intelligence dashboards, reports, and visualizations using Tableau, Power BI, QuickSight, or Cognos. - Perform data analysis to identify trends, business opportunities, operational gaps, and performance improvements. - Define, track, and monitor KPIs and business metrics to support strategic objectives. - Collaborate with Data Engineering, Product, Program, and Business teams to deliver analytics and reporting solutions. - Conduct root cause analysis and provide data-driven recommendations for business challenges. - Support healthcare analytics, pricing analysis, operational reporting, and business performance initiatives. - Build and optimize SQL queries for data extraction, validation, and reporting purposes. - Ensure data governance, data quality, security, and compliance standards are maintained. - Drive reporting automation and process optimization initiatives to improve efficiency and productivity. - Prepare executive dashboards, presentations, and analytical insights for leadership teams. - Participate in Agile ceremonies, stakeholder meetings, sprint planning, and requirement discussions. Qualifications - Strong expertise in SQL and Advanced Excel. - Hands-on experience with Tableau, Power BI, QuickSight, or Cognos. - Experience working in multi-cloud environments including AWS and GCP. - Strong experience with AWS services such as Redshift, Athena, S3, and Glue. - Understanding of ETL/ELT processes, Data Warehousing, and Data Modeling concepts. - Familiarity with Python, R, or analytics scripting is an added advantage. - Healthcare domain experience is preferred. - Experience working with healthcare analytics, Revenue Cycle Management, operational reporting, or healthcare data platforms is an added advantage. - Strong communication and presentation skills. - Stakeholder management and cross-functional collaboration. - Strong analytical and problem-solving abilities. - Ability to work effectively in fast-paced and ambiguous environments. Requirements - Strong expertise in SQL and Advanced Excel. - Hands-on experience with Tableau, Power BI, QuickSight, or Cognos. - Experience working in multi-cloud environments including AWS and GCP. - Strong experience with AWS services such as Redshift, Athena, S3, and Glue. - Understanding of ETL/ELT processes, Data Warehousing, and Data Modeling concepts. - Familiarity with Python, R, or analytics scripting is an added advantage. Benefits - Candidate should be comfortable working remotely in EST time zone.

• Lead analytical efforts to drive data informed decision-making across the entire organization • Gather, analyze, and visualize / present technical insurance data • Collaborate with data engineering, insurance product, claims, finance and operations teams to improve data integrity and automate reporting capabilities using VBA, SQL and Python • Transform complex insurance data into clear, compelling insights for both technical and non-technical stakeholders through required reporting and data visualization • Conduct deep-dive data analysis, develop analytical tools, deliver dedicated solutions to help other departments automate their workflows, and identify opportunities to enhance business performance and operational effectiveness • Provide ad hoc analytical support and research as needed to ensure Ledgebrook continues to operate with data-driven precision.

• Transform complex business data into meaningful insights that support strategic decision-making across the Credit Union. • Partner with business leaders to develop enterprise reporting solutions and identify trends and opportunities. • Deliver data-driven recommendations to improve operational performance and enhance the member experience. • Design, develop, and maintain enterprise Tableau dashboards, executive scorecards, and performance indicator (KPI) reporting. • Analyze large volumes of financial, operational, lending, and member data to identify trends and actionable business insights. • Present analytical findings through professional visualizations and executive-level presentations that facilitate informed decision-making. • Promote best practices related to data quality, reporting standards, and documentation.

• Partner with cross-functional teams, including Marketing, Finance, Product, Sales, Medical Affairs, and Customer Success, to understand business needs and deliver actionable analyses. • Proactively explore data to identify patterns, trends, and opportunities that can drive business growth and operational improvements. • Define and manage data collection requirements across systems and functions to support consistent reporting and insight generation. • Develop, optimize, and automate data pipelines using structured query language (SQL), artificial intelligence, and modern data engineering tools to deliver timely, accurate reporting at scale. • Build and maintain robust, interactive dashboards that enable self-service reporting across go-to-market and product teams. • Identify opportunities to improve processes, reduce manual work, and drive efficiencies across the data landscape. • Translate complex data into clear, compelling visualizations and presentations for diverse audiences, including executives and external partners. • Partner with data scientists, analysts, and engineers to improve data quality, reporting accuracy, and analytical consistency across the organization.