Data Quality Analyst – Validation and Reconciliation

The Elite Job; Town of Geneseo (NY); Hybrid; USD 65,000 - 90,000; Full time

Benefits offered by this job

Flexible work arrangements

Professional development opportunities

Performance-based recognition

Career growth potential

Collaborative work environment

Job summary

The Elite Job seeks a Data Quality Analyst – Validation and Reconciliation to ensure data accuracy, completeness, and reliability across systems and reports. You will review datasets, validate information, and reconcile discrepancies, turning findings into actionable insights.

You will collaborate with data partners, finance, operations, and IT to resolve data issues and improve procedures. Proficiency in Excel, SQL, and BI tools will help support reporting integrity and governance.

Qualifications

• Bachelor's degree preferred or equivalent practical experience.
• Strong understanding of data quality: accuracy, completeness, consistency, timeliness.
• Experience with validation, reconciliation, and data governance concepts.
• Proven ability to work with large datasets and document findings clearly.
• Willingness to learn new data tools and processes.

Responsibilities

• Validate data from multiple sources to ensure accuracy and completeness.
• Reconcile records across databases and reporting platforms.
• Identify data quality issues and coordinate corrective actions.
• Develop quality reports, reconciliation trackers, and exception logs.
• Summarize findings for technical and non-technical stakeholders.
• Support process improvements and documentation efforts.

Skills

Data quality principles

Attention to detail

Data analysis

Excel proficiency

SQL basics

Communication

Problem solving

Documentation

Cross-functional collaboration

Education

Bachelor's degree preferred

Tools

Power BI

SQL

Excel

Job description

Job Summary

The Elite Job is seeking a detail-oriented and analytical Data Quality Analyst – Validation and Reconciliation to support the accuracy, consistency, completeness, and reliability of business data across multiple systems and reporting platforms. The successful candidate will play a vital role in maintaining high data quality standards by reviewing datasets, validating information, reconciling discrepancies, investigating data inconsistencies, and ensuring that business records meet established quality requirements.

In this role, the Data Quality Analyst will collaborate with data analysts, business stakeholders, finance teams, operations professionals, database administrators, and technical teams to identify data issues and implement effective corrective actions. The position requires a structured approach to data validation, a strong understanding of reconciliation processes, and the ability to transform complex data findings into clear, actionable insights.

The ideal candidate will be comfortable working with spreadsheets, databases, reporting tools, and data management systems. They should be capable of identifying missing values, duplicate records, formatting inconsistencies, calculation errors, and mismatches between source systems and target reports.

The role offers an opportunity to contribute to data-driven decision-making, improve operational efficiency, strengthen reporting reliability, and support continuous improvement across the organization. Candidates who demonstrate accuracy, accountability, problem-solving ability, and a commitment to data integrity are encouraged to apply.

Key Responsibilities

Data Validation and Quality Assurance

• Validate data collected from internal databases, external sources, business applications, and operational systems to ensure accuracy and completeness.
• Review datasets against established business rules, quality standards, validation criteria, and reporting requirements.
• Identify missing information, incorrect values, duplicate entries, inconsistent formats, and other data quality issues.
• Perform routine and ad hoc quality checks before data is used for reporting, analytics, financial reconciliation, or operational decision-making.
• Verify that data transformations, calculations, and updates produce accurate and consistent results.
• Maintain clear documentation of validation procedures, testing results, identified defects, and corrective actions.

Data Reconciliation and Discrepancy Resolution

• Reconcile records across multiple databases, spreadsheets, source systems, and reporting platforms to identify differences and inconsistencies.
• Compare source data with target records to verify that information has been transferred, processed, and recorded correctly.
• Investigate mismatched totals, missing transactions, duplicate records, unexpected variances, and conflicting data values.
• Work with relevant departments to determine the root causes of discrepancies and coordinate appropriate resolutions.
• Verify corrected records and conduct follow-up checks to ensure that identified issues have been resolved successfully.
• Prepare reconciliation summaries and exception reports that explain outstanding differences, their potential impact, and recommended next steps.

Data Analysis and Reporting

• Use Microsoft Excel, SQL, and other appropriate analytical tools to examine datasets and identify unusual patterns or errors.
• Develop and maintain quality reports, reconciliation trackers, exception logs, and performance dashboards.
• Monitor key data quality indicators, including accuracy, completeness, consistency, validity, uniqueness, and timeliness.
• Summarize findings for technical and non-technical stakeholders using clear explanations and supporting evidence.
• Assist in preparing periodic reports that demonstrate data quality performance, recurring issues, and improvement opportunities.
• Support data analysis activities by ensuring that information used in reports and dashboards is dependable and fit for purpose.

Process Improvement and Documentation

• Review existing validation and reconciliation procedures and recommend improvements to increase efficiency and reduce manual errors.
• Help develop standardized checklists, data quality rules, operating procedures, and reconciliation templates.
• Identify opportunities to automate repetitive validation tasks using formulas, SQL queries, scripts, or approved data tools.
• Maintain accurate records of quality checks, exceptions, investigation outcomes, and resolution status.
• Contribute to the development of repeatable quality assurance processes that support consistent results across teams.
• Participate in continuous improvement initiatives focused on data governance, reporting accuracy, and operational reliability.

Collaboration and Stakeholder Support

• Work closely with data management, finance, operations, reporting, and technology teams to resolve data-related challenges.
• Communicate discrepancies promptly and provide clear recommendations for corrective action.
• Assist business users in understanding data quality requirements and applying appropriate validation practices.
• Support internal reviews, compliance checks, and audit-related requests by providing accurate documentation when required.
• Handle confidential business information responsibly and follow company policies relating to data access, privacy, and information security.
• Meet agreed deadlines while maintaining high standards of accuracy and professionalism.

Required Skills and Qualifications

• A bachelors degree in Computer Science, Information Technology, Data Analytics, Statistics, Mathematics, Business Analytics, Accounting, Finance, or a related field is preferred.
• Equivalent practical experience, relevant training, or demonstrated analytical ability may also be considered.
• Good understanding of data quality principles, including accuracy, completeness, consistency, validity, uniqueness, and timeliness.
• Strong attention to detail and the ability to identify discrepancies in large datasets.
• Proficiency in Microsoft Excel, including sorting, filtering, lookup functions, conditional formatting, pivot tables, and data comparison techniques.
• Basic to intermediate SQL knowledge for retrieving, comparing, filtering, and validating database records is desirable.
• Familiarity with data reconciliation, exception handling, data cleansing, and quality assurance procedures.
• Strong analytical thinking and the ability to investigate problems systematically.
• Excellent organizational skills and the ability to manage multiple validation tasks simultaneously.
• Clear written and verbal communication skills for documenting findings and explaining data issues.
• Ability to work independently while collaborating effectively with cross-functional teams.
• A responsible approach to handling sensitive information and maintaining data confidentiality.
• Willingness to learn new data tools, business systems, and quality management processes.

Experience

Entry‑Level Candidates

Fresh graduates and candidates with limited professional experience may be considered if they demonstrate strong numerical reasoning, attention to detail, spreadsheet skills, and a willingness to learn data validation and reconciliation procedures.

Experienced Candidates

Candidates with approximately 1–3 years of experience in data quality analysis, data entry quality control, reporting, database administration support, financial reconciliation, business operations, or quality assurance will be well suited to the position.

Relevant experience may include:

• Validating records and identifying inconsistencies in business datasets.
• Reconciling information between spreadsheets, databases, or enterprise systems.
• Preparing data quality reports and maintaining exception logs.
• Using Excel or SQL to compare records and investigate data discrepancies.
• Supporting data cleansing, reporting accuracy, audit preparation, or process improvement initiatives.
• Experience with Power BI, Tableau, Python, ETL processes, or automated data quality tools is an advantage but may not be essential for every assignment.

Candidates should be able to demonstrate a methodical approach to problem-solving, a commitment to accuracy, and the ability to learn established business procedures.

Working Hours

• Employment Schedule: Full-time, subject to the specific role and client requirements.
• Typical Working Hours: Approximately 40 hours per week, depending on the applicable employment arrangement.
• Working Days: Generally Monday to Friday, with schedules determined by business needs.
• Work Arrangement: Remote, hybrid, or on‑site opportunities may be available depending on the position.
• Shift Requirements: Some assignments may require flexible hours or coordination with international teams across different time zones.
• Breaks and Leave: Applicable breaks, holidays, and leave entitlements will follow the relevant company policies and local employment regulations.
• Overtime: Any additional hours will be managed in accordance with the applicable employment terms and legal requirements.

Candidates should be comfortable managing deadlines, organizing their daily workload, and maintaining consistent productivity during scheduled working hours. Final working arrangements will be communicated during the recruitment process.

Knowledge, Skills, and Abilities

Technical Knowledge

• Understanding of relational databases, structured datasets, and common data formats.
• Knowledge of data validation rules, reconciliation methods, and data cleansing practices.
• Familiarity with spreadsheet-based analysis and database querying.
• Awareness of data governance principles, documentation standards, and information security practices.
• Basic understanding of data pipelines, source-to-target mapping, and reporting workflows is beneficial.

Analytical Skills

• Ability to compare datasets and identify differences accurately.
• Capacity to investigate unusual results and determine likely root causes.
• Strong numerical reasoning and logical thinking.
• Ability to recognize patterns, trends, duplicate entries, missing records, and inconsistent values.
• Confidence in assessing the significance of discrepancies and prioritizing issues according to their potential impact.

Organizational Abilities

• Ability to manage multiple assignments while maintaining accuracy.
• Strong time-management skills and a systematic approach to completing repetitive tasks.
• Ability to maintain organized documentation and track issues through resolution.
• Commitment to following standard procedures and meeting agreed deadlines.

Communication and Teamwork

• Ability to communicate technical findings in straightforward business language.
• Confidence in asking relevant questions and clarifying data requirements.
• Ability to collaborate with colleagues from technical and non-technical backgrounds.
• Professionalism when discussing errors, reporting discrepancies, and recommending improvements.

Personal Attributes

• High attention to detail and a strong sense of responsibility.
• Integrity when handling business information.
• Patience and persistence when investigating complex discrepancies.
• Adaptability when working with new systems, datasets, and procedures.
• A continuous learning mindset and a proactive approach to improving work quality.

Benefits

• Flexible Work Arrangements: Opportunities for remote or hybrid work where supported by the position.
• Professional Development: Access to relevant training, learning resources, and opportunities to strengthen data analysis skills.
• Technical Skill Development: Practical exposure to spreadsheet analysis, SQL, reporting systems, reconciliation processes, and data quality methodologies.
• Career Growth Opportunities: Potential progression into senior data quality, data analytics, business intelligence, data governance, or data operations roles.
• Collaborative Work Environment: Opportunities to work with professionals across business, technology, finance, and operations functions.
• Performance Recognition: Recognition for reliable delivery, process improvements, and contributions to data quality objectives, where provided under company policy.
• Employee Leave and Holidays: Applicable leave entitlements and public holidays in accordance with the relevant employment terms and local laws.
• Compensation and Other Benefits: Salary, insurance, retirement benefits, allowances, or other employment benefits, where applicable, will be communicated during recruitment.

Actual compensation, benefits, equipment provision, and remote-work arrangements will depend on the confirmed vacancy and employment agreement. No particular benefit should be assumed unless it is included in the official offer.

Why Join The Elite Job?

Joining The Elite Job as a Data Quality Analyst – Validation and Reconciliation offers an opportunity to build a career in a field where accuracy, accountability, and reliable information are essential to business success.

The role is suitable for professionals who enjoy working with data, solving problems, improving processes, and helping organizations make better-informed decisions. By ensuring that business records and reports are accurate and consistent, you can contribute directly to operational efficiency and the quality of organizational insights.

• Develop Valuable Analytical Skills: Strengthen your practical knowledge of data validation, reconciliation, Excel, SQL, reporting, and data quality management.
• Build a Foundation for Career Growth: Gain experience that can support future opportunities in data analytics, business intelligence, data governance, database support, and quality assurance.
• Make a Meaningful Contribution: Help reduce data errors, improve reporting confidence, and support dependable business operations.
• Work Across Business Functions: Collaborate with different teams to understand data requirements, resolve inconsistencies, and improve information management practices.
• Learn Through Practical Challenges: Develop your problem-solving capabilities by working with real-world data quality issues and structured reconciliation processes.
• Contribute to Continuous Improvement: Help introduce better validation methods, improve documentation, and identify opportunities to reduce repetitive manual work.

The Elite Job encourages candidates who value precision, continuous learning, and professional development to apply. The organization aims to consider candidates based on relevant skills, qualifications, experience, and the requirements of the available position.