Data Analyst

• Architected and optimized complex SQL based validation frameworks to ensure completeness of data, integrity, and consistency across multiple enterprise systems.

• Led end-to-end source-to-target reconciliation initiatives, identifying data breaks, root causes, and control gaps across large-scale datasets.

• Designed and developed executive-ready reconciliation dashboards and operational KPI views to monitor data quality trends, exception volumes, and processing health.

• Automated reconciliation and validation workflows using Python (Pandas, notebooks, scripting), significantly reducing manual effort and improving auditability.

• Built scalable Power Apps solutions and workflow automations to streamline reconciliation intake, exception triage, approval workflows, and operational tracking.

• Defined and maintained robust documentation standards including SOPs, reconciliation logic, validation frameworks, and data dictionaries to support operational continuity and governance readiness.

• Partnered cross-functionally with business, operations, and engineering teams to translate data issues into actionable remediation plans and long-term quality improvements.

• Presented reconciliation insights, risk assessments, and governance updates to both technical stakeholders and business leadership.

Required Skills

• Advanced SQL Expertise: Strong command of complex SQL development including CTEs, window functions, performance optimization, aggregation reconciliation, and large-scale data validation.

• Data Validation & Reconciliation: strong understanding of reconciliation approaches, exception handling, controls, and root-cause analysis.

• Dashboard & Reporting Development: Proven experience building operational and executive dashboards with drill-down analysis, KPI tracking, and actionable visual insights.

• Python: Hands-on expertise in Python-based automation using Pandas and notebook-driven workflows for repeatable data validation and exception reporting.

• Power Platform Enablement: Experience developing lightweight operational applications and workflow solutions using Power Apps and related Microsoft Power Platform capabilities.

• Communication: excellent written and verbal communication; able to translate technical findings into actionable business insights.

• Problem Solving: strong analytical mindset with attention to detail and the ability to manage multiple priorities.

• Large Dataset Processing: Experience handling and reconciling high-volume datasets across enterprise platforms with focus on scalability, performance, and accuracy.

• Data Quality Frameworks: Knowledge of data quality controls including completeness, uniqueness, consistency, validity, and reconciliation rule design.

• Variance & Exception Analysis: Strong capability in identifying data anomalies, investigating reconciliation breaks, and driving root-cause remediation.

• Performance Optimization: Ability to optimize SQL queries, validation logic, and reconciliation routines for large-scale enterprise data environments.

• Control & Audit Readiness: Familiarity with SOX-aligned controls, audit support processes, reconciliation governance, and operational risk management.

• Data Mapping & Lineage: Experience understanding source-to-target mappings, transformation logic, lineage tracking, and cross-system dependencies.

• Enterprise Data Platforms: Exposure to modern data ecosystems such as Databricks, Microsoft Fabric, cloud data warehouses, or enterprise reporting environments.

• Operational Monitoring: Ability to build monitoring frameworks and automated alerting mechanisms for reconciliation failures and data quality issues.

• Automation & Workflow Optimization: Experience reducing manual reconciliation effort through automation, workflow orchestration, and reusable validation frameworks.

• Data Governance & Compliance: Understanding of enterprise governance standards, access controls, sensitive data handling, and compliance-oriented data operations.

• Analytical Storytelling: Ability to convert reconciliation findings into meaningful operational insights and executive-level summaries.

• Cross-System Integration Understanding: Familiarity with APIs, flat files, ETL pipelines, ERP systems, and enterprise application integrations.

• Bachelor’s degree in computer science, Information Systems, Engineering, Statistics, Finance, or a related field (or equivalent practical experience).

• 2–6 years of experience in data validation, analytics, reporting, or reconciliation-focused roles (flexible based on overall skill fit).

• Demonstrated experience working with large datasets and collaborating across business and technical teams.

• Experience with BI tools (e.g., Power BI or similar) for building interactive dashboards and publishing reports.

• Knowledge of ETL/ELT concepts and data pipelines; familiarity with data quality frameworks and monitoring.

• Understanding of data governance, and control-minded reconciliation practices.

• Exposure to APIs, connectors, or integration patterns to source reconciliation inputs.

• Domain experience in finance operations, supply chain, sales operations, or other data-intensive business functions.

Soft Skills & Competencies

• Clear, concise communicator with the ability to tailor messaging to different audiences.

• Strong stakeholder management and collaboration skills; comfortable working in ambiguity.

• High ownership mindset with a bias for action and continuous improvement.

• Detail-oriented with strong documentation discipline and follow-through.

• Able to balance speed and accuracy while maintaining data integrity and control standards.