Data Analyst

• SQL: Advanced querying for profiling and validation.
• Excel: Advanced data manipulation and analysis.
• Power BI: Business user level for validation and navigation.
• Data Disciplines: Data Profiling, Validation, Reconciliation, and Mapping.
• Tools: Jira / Azure DevOps for agile tracking.
• Analytical & Communication Skills
• Analysis: Process Analysis, KPI Definition, Root Cause Analysis.
• Communication: Translating technical data concepts for the PO and business audiences, detailed technical writing for engineering teams.

Job Responsibilities:

• Data Requirements & Analysis.
• Support the Product Owner by translating high-level business requirements and user stories into detailed data and reporting specifications.
• Participate in requirement workshops alongside the PO to understand business processes, core metrics, and data expectations.
• Provide technical data insights and feasibility assessments to the PO to support backlog refinement.
• Source System Analysis.
• Analyze source systems and datasets to identify available data elements and business attributes needed to fulfill the PO’s user stories.
• Assess data quality, completeness, and historical availability.
• Perform data profiling and gap analysis to inform reporting feasibility.
• Example Deliverables: Source Inventory, Data Availability Assessment, Source System
• Documentation, Data Gap Analysis.
• Source-to-Target Mapping.
• Create and maintain detailed Source-to-Target (S2T) mapping documentation.
• Define business attribute mappings from source systems to target datasets (e.g., Databricks).
• Document data transformation rules and business definitions.
• Work collaboratively with Data Engineers to validate that mapping implementation matches the documented logic.
• Data Validation & Reconciliation Support.
• Support data validation activities across reporting layers (Source vs. Data Platform, Semantic Model, and Report levels).
• Analyze discrepancies, variances, and data issues.
• Assist QA teams in reconciliation efforts and support root-cause analysis for data defects.
• User Acceptance Testing (UAT) Support.
• Prepare detailed data validation criteria and expected results based on the PO''s acceptance criteria.
• Execute data-focused test cases to ensure accuracy before full business UAT.
• Document data defects and assist the PO in reviewing dashboards and reports for calculation accuracy.
• Assist the PO with technical data explanations during stakeholder reviews and demos.
• Documentation & Governance.
• KPI Catalog & Data Dictionary: Maintain a centralized repository of definitions.
• Source-to-Target Mapping Documents: Keep mappings updated as requirements evolve.
• Data Profiling Summaries: Document source system findings.
• Data Validation & Reconciliation Reports: Provide evidence of data accuracy.