TOPS-DCFS-Senior Conversion Data Analyst (Matrix)

Senior Conversion Data Analyst Role Description

Role Title

Senior Conversion Data Analyst

Position Description

The Senior Conversion Data Analyst will play a critical role in bridging the gap between business stakeholders and technical teams to deliver data-driven solutions that align with organizational objectives. The role requires an experienced professional with a proven ability to elicit, analyze, and document business and technical requirements, translate them into actionable user stories, and ensure seamless execution within an Agile framework. The successful candidate will possess strong analytical, techno-functional, and communication skills to influence cross-functional teams and drive data quality, process improvements, and informed decision-making.

Essential Duties and Responsibilities

Requirements Elicitation & User Stories: Collaborate with stakeholders to gather, analyze, and document functional and technical requirements. Develop clear, concise, and testable Agile user stories that accurately reflect business needs. Data Analysis & Insights: Conduct in-depth data analysis to identify trends, patterns, and opportunities that drive strategic and operational decisions. Test Case Development: Define, develop, and manage comprehensive test cases to validate requirements and ensure the quality and accuracy of data solutions. Stakeholder Communication: Translate complex technical and analytical concepts into simple, actionable insights for business stakeholders. Provide regular updates, reports, and presentations to ensure alignment. Agile Delivery: Actively participate in Agile ceremonies, contributing to backlog refinement, sprint planning, and iteration reviews. Partner with Product Owners, Scrum Masters, and technical teams to deliver high-quality solutions on time. Technical & Functional Collaboration: Engage in discussions with data engineers, architects, and business users to ensure accurate understanding of both functional requirements and underlying technical components. Process & Data Quality Improvement: Recommend and implement improvements in data quality, governance, and operational processes to enhance data reliability and usability. Documentation & Knowledge Sharing: Maintain detailed documentation of requirements, user stories, test cases, and process flows to ensure transparency and reproducibility.

Optional

Experience and Education Requirements

Bachelor’s degree in computer science, Statistics, Mathematics, Data Science, or related field (Master’s preferred). Minimum of 8+ years as a Business Analyst on projects of similar size and complexity, with significant experience in data-centric and analytics-driven initiatives. Proven experience with relational databases (SQL Server, PostgreSQL, Oracle) and data querying techniques. Experience working with large, complex datasets in a cloud-based or on-premises environment.

Knowledge, Skills, and Abilities

Experience: Minimum of 8+ years as a Business Analyst, preferably on data-focused or analytics-driven projects of comparable complexity. Agile Expertise: Extensive experience working within Agile frameworks, including writing user stories and defining acceptance criteria. Data Conversion Projects: Proven experience leading or supporting large-scale data conversion, migration, or transformation projects. Azure Data Factory: Hands-on experience with Azure Data Factory for building, orchestrating, or monitoring data pipelines. Advanced SQL Proficiency: Expertise in SQL for data extraction, joins, aggregations, and performance tuning. Advanced Excel & BI Tools: Advanced expertise in Excel (complex formulas, pivot tables, macros) and/or BI tools (Power BI preferred; both highly desirable). Data Warehousing & ETL: Strong understanding of data warehousing concepts, dimensional modeling, and ETL processes. Cloud Data Platforms: Familiarity with cloud-based data platforms such as Azure Data Lake, AWS Redshift, or Google Big Query. Data Governance: Experience with data governance, data quality frameworks, and metadata management is advantageous. Analytical & Problem-Solving Skills: Exceptional critical thinking and problem-solving capabilities, with a focus on delivering actionable insights. Communication Skills: Outstanding written and verbal communication skills, with the ability to simplify complex technical concepts for diverse audiences. Organization & Independence: Highly organized, detail-oriented, and capable of managing multiple priorities independently in fast-paced environments.