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.

Requirements

Bachelors degree in computer science Information Systems Engineering Statistics Finance or a related field (or equivalent practical experience).

26 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.