Data Analyst

NetWeb Software ISO 008 Certified; Vadodara; On-site; INR 700,000 - 1,200,000; Full time

Job summary

NetWeb Software ISO 008 Certified is seeking an experienced Senior Data Quality Analyst to join our Enterprise Data team. This role ensures the integrity, consistency, and accuracy of business-critical data across multiple enterprise applications, with a focus on SQL-based investigation and data reconciliation.

The ideal candidate will have strong SQL expertise, attention to detail, and the ability to collaborate with business and technical teams to resolve data quality issues, validate changes,

Qualifications

• 5–6+ years of experience in Data Analysis or Data Quality.
• Strong experience with SQL Server or other enterprise relational databases.
• Experience working with CRM, ERP, EDW, or enterprise operational systems.
• Exposure to Power BI for validating and consuming data is an advantage, though this is not a dashboard development role.
• Exceptional analytical and investigative skills.
• Strong attention to detail.
• Ability to solve complex data problems independently.
• Strong ownership and accountability.

Responsibilities

• Perform detailed analysis of business data across enterprise systems.
• Identify inconsistencies, missing records, duplicates and data mapping issues.
• Investigate discrepancies in customer, product, shipment, and invoice data.
• Understand data flow between applications to locate root causes.
• Write SQL queries for data validation and reconciliation.
• Validate changes after updates and deployments.
• Produce reconciliation reports and data quality metrics.

Skills

Analytical skills

Attention to detail

Independent problem solving

Ownership & accountability

Investigative mindset

Prioritization

Tools

SQL Server

Power BI

CRM/ERP/EDW

Job description

We are seeking an experiencedSenior Data Quality Analyst to join our Enterprise Data team. This role isresponsible for ensuring the integrity, consistency, and accuracy ofbusiness-critical data across multiple enterprise applications.

The ideal candidate is someone whoenjoys investigating complex data issues, performing deep data analysis usingSQL, identifying the root causes of inconsistencies, and collaborating withboth business and technical teams to ensure enterprise data remains accurateand reliable.

This is a highly analytical rolethat requires strong SQL expertise, exceptional attention to detail, and theability to understand how data flows between multiple enterprise systems.

Key Responsibilities

Enterprise Data Investigation

• Perform detailed analysis ofbusiness data across multiple enterprise systems, vendor data sources, andoperational databases.
  
• Compare records across systems toidentify inconsistencies, missing records, duplicate records, incorrectmappings, and synchronization failures.
  
• Investigate discrepancies relatedto customer information, product information, shipment dates, invoicedates, warranty dates, pricing, serial numbers, and otherbusiness-critical data elements.
  
• Understand relationships betweendifferent enterprise applications and identify where incorrect dataoriginates.
  

SQL-Based Data Analysis

• Write complex SQL queries toanalyze large datasets and compare information between multiple databases.
  
• Perform data reconciliationbetween various systems of record.
  
• Build reusable SQL scripts fordata validation and reconciliation.
  
• Analyze historical data trends toidentify recurring data quality issues.
  
• Validate database changes afterupdates, scripts, or production deployments.
  
• Work with large transactionaldatasets while ensuring query efficiency and performance.
  

Data Quality & Root CauseAnalysis

• Investigatedata anomalies reported by Sales Operations, Business Teams, CustomerSupport, and other stakeholders.
  
• Perform rootcause analysis to determine whether issues originate from:
  
• Sourcesystems
  
• ETLprocesses
  
• Userinput
  
• Databasescripts
  
• Businessprocess gaps
  
• Documentfindings and recommend corrective actions.
  
• Ensure thatdata quality issues are permanently resolved rather than repeatedlycorrected.
  
• Analyze vendor-provided files andcompare them with enterprise application data.
  
• Verify that integrations correctlyupdate the BOM application.
  
• Identify records that failvalidation during imports.
  
• Work with integration teams toresolve mapping and transformation issues.
  
• Validate incoming files before and after processing.
  
• Ensure all enterprise systemsmaintain consistent and synchronized information.
  
• Produce reconciliation reportshighlighting mismatches and recommended actions.
  

Quality Assurance

• Verify production fixes.
  
• Supportregression validation for data-related changes.
  

Stakeholder Collaboration

• Work closely with:
  
• Business Users
  
• Database Administrators
  
• Integration Teams
  
• Application DevelopmentTeams
  
• Gather business context behindreported issues.
  
• Present investigation findings andrecommend appropriate corrective actions.
  
• Translate technical findings intobusiness-friendly language.
  

Documentation & Reporting

• Document investigationresults and root cause findings.
  
• Prepare validation reportsafter database updates.
  
• Document recurring issues andrecommend long-term improvements.
  
• Maintain data quality metricsand trend analysis.
  

Requirements

Preferred Experience

• 5–6+ years of experience in DataAnalysis or Data Quality.
  
• Strong experience with SQLServer or other enterprise relational databases.
  
• Experience working with CRM,ERP, EDW, or enterprise operational systems.
  
• Experience supporting SalesOperations or Order Management functions.
  
• Familiarity with ETL andenterprise data integration processes.
  
• Exposure to Power BI forvalidating and consuming data is an advantage, though this is not adashboard development role.
  
• Exceptional analytical andinvestigative skills.
  
• Strong attention to detail.
  
• Ability to solve complex dataproblems independently.
  
• Strong ownership andaccountability.
  
• Ability to prioritizemultiple investigations in a fast-paced environment.
  
• Continuous improvementmindset focused on enhancing data quality and governance.