Data Analyst

This role focuses on building and supporting enterprise-level analytics solutions using Power BI and semantic data modeling. You will work with curated datasets to create standardized, high-performance dashboards aligned with DCAM and FIRM reporting frameworks.

You'll collaborate with business stakeholders to gather requirements, design data models, define metrics, and deliver end-to-end reporting solutions. A strong understanding of maintenance and work order systems (like SAP S/4HANA, JDE, or InforEAM) is important to translate operational needs into actionable insights.

The role also involves owning ongoing reporting operations, including data validation, troubleshooting issues, and enhancing dashboards based on evolving business needs.

Key Responsibilities

· Work closely with business stakeholders to gather, analyze, and document functional and data requirements for AI solutions.

· Create clear and structured Business Requirement Documents (BRDs), Functional Specifications, and user stories.

· Define detailed acceptance criteria to ensure alignment between business expectations and delivered AI capabilities.

· Partner with Data Science, Engineering, and Product teams to clarify requirements and manage scope changes.

· Perform functional validation, QA testing, and output verification for AI/ML models and data-driven applications.

· Identify gaps, inconsistencies, and risks in AI solution design and recommend improvements.

· Support UAT planning and execution, ensuring smooth stakeholder sign-off.

· Track defects, monitor resolution progress, and ensure delivery quality standards are met.

· Prepare dashboards, reports, and insights to measure solution performance and adoption.

Required Skills & Qualifications

· 4–6 years of experience as a Data Analyst, preferably in analytics or AI-driven environments.

· Strong experience in requirement gathering, documentation, and acceptance criteria definition.

· Hands-on experience in QA validation and UAT coordination.

· Good understanding of AI / Machine Learning lifecycle and data workflows.

· Strong analytical thinking and problem-solving skills.

· Excellent stakeholder communication and coordination abilities.

· Experience with tools such as SQL, Excel, Jira, Confluence, or similar tracking platforms.

Preferred Skills

· Exposure to Python, data visualization tools (Tableau / Power BI), or model performance metrics.

· Understanding of data quality frameworks and validation techniques.

· Experience working in Agile / Scrum delivery environments.

Success Metrics

· Quality and clarity of documented requirements and acceptance criteria.

· Accuracy and reliability of AI solution validation.

· Timely UAT completion and stakeholder satisfaction.

· Reduction in post-release defects and improved solution adoption.