Job Description

Seeking a detail-oriented analyst to validate and reconcile data across systems by writing SQL queries, automating checks using Python, and building reconciliation dashboards. This role partners with business and technical stakeholders to identify breaks, explain variances, and drive data quality improvements using tools such as Power Apps and reporting platforms.

Key Responsibilities

Architected and optimized complex SQL based validation frameworks to ensure completeness of data, integrity, and consistency across multiple enterprise
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
Built scalable Power Apps solutions and workflow automations to streamline reconciliation intake, exception triage, approval workflows, and operational
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
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 S Reconciliation: strong understanding of reconciliation approaches, exception handling, controls, and root-cause analysis.
Dashboard S Reporting Development: Proven experience building operational and executive dashboards with drill-down analysis, KPI tracking, and actionable visual
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.

Additional Technical & Analytical Skills

Large Dataset Processing: Experience handling and reconciling high-volume datasets across enterprise platforms with focus on scalability, performance, and
Data Quality Frameworks: Knowledge of data quality controls including completeness, uniqueness, consistency, validity, and reconciliation rule
Variance S 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 S Audit Readiness: Familiarity with SOX-aligned controls, audit support processes, reconciliation governance, and operational risk management.
Data Mapping S 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 S Workflow Optimization: Experience reducing manual reconciliation effort through automation, workflow orchestration, and reusable validation
Data Governance S 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.

Preferred Skills

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
Exposure to APIs, connectors, or integration patterns to source reconciliation
Domain experience in finance operations, supply chain, sales operations, or other data-intensive business functions. Bachelor’s degree in computer science, Information Technology, or related field.

Qualifications

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

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Job Title : Data Analyst