Data Quality Analyst

About the Role

Amoha Recruitment Services is a US-focused staffing and placement firm building a talent pipeline of Data Quality Analysts for client engagements across various industries. This opportunity is ideal for detail-oriented candidates interested in ensuring the accuracy, completeness, consistency, and reliability of business-critical information.

Key Responsibilities

• Validate datasets for accuracy, completeness, consistency, and reliability.
• Perform data quality checks to identify missing values, duplicate records, incorrect formats, and inconsistencies.
• Write and execute SQL queries to validate, reconcile, and analyze data across databases.
• Conduct data profiling to understand data structures, patterns, anomalies, and quality issues.
• Investigate data discrepancies and collaborate with technical and business teams to identify root causes.
• Support data cleansing, standardization, deduplication, and remediation activities.
• Develop and maintain data quality rules, validation procedures, and test cases.
• Compare data across source systems, databases, reports, and data warehouse environments.
• Assist with ETL (Extract, Transform, Load) testing and data pipeline validation.
• Verify data transformations and business logic for accurate downstream reporting.
• Prepare data quality reports, dashboards, and documentation to communicate findings.
• Monitor data quality metrics and identify recurring data issues.
• Collaborate with data engineers, business analysts, QA teams, and data governance teams.
• Support data audits and compliance-related quality checks.
• Maintain documentation for data definitions, business rules, validation logic, and issue resolution.
• Recommend process improvements and automation opportunities to enhance data quality.
• Assist with regression testing for data pipelines, applications, or database structure changes.

Requirements & Tech Stack

• Basic to intermediate SQL skills, including SELECT statements, JOINs, filtering, aggregation, and subqueries.
• Understanding of relational databases, tables, schemas, primary keys, and foreign keys.
• Familiarity with data validation, data profiling, data cleansing, and data reconciliation concepts.
• Understanding of data quality dimensions: accuracy, completeness, consistency, uniqueness, validity, and timeliness.
• Familiarity with Excel or Google Sheets for data analysis, validation, and reporting.
• Basic understanding of ETL processes, data integration, and data warehouse concepts.
• Ability to identify anomalies, investigate discrepancies, and document findings clearly.
• Strong analytical thinking, attention to detail, and problem-solving skills.
• Good written and verbal communication skills.
• Ability to collaborate with technical and non-technical stakeholders.
• Willingness to learn data quality tools, database technologies, and industry best practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Analytics, Data Science, Statistics, Mathematics, Information Systems, or a closely related field.
• 0–3 years of professional, internship, academic, or hands-on experience in data quality, data analysis, database testing, data validation, or a related area.

Skills That Strengthen Your Application

• SQL and relational databases
• Microsoft Excel, PivotTables, lookup functions, and data validation
• Python for data analysis and validation automation
• Data profiling and data cleansing
• Data reconciliation and duplicate detection
• ETL testing and data pipeline validation
• Data warehouse and database fundamentals
• Data quality metrics, rules, and scorecards
• Power BI, Tableau, or other reporting tools
• Informatica Data Quality or Informatica PowerCenter
• Talend Data Quality and data integration tools
• Great Expectations or similar data validation frameworks
• dbt testing and data transformation validation
• Snowflake, Amazon Redshift, or Google BigQuery
• Microsoft SQL Server, PostgreSQL, Oracle, or MySQL
• Cloud data platforms: AWS, Microsoft Azure, or Google Cloud
• Jira, Confluence, and defect-tracking workflows
• Root-cause analysis and issue management
• Data governance, metadata management, and data lineage
• Data integrity and master data management (MDM)
• Data privacy and compliance fundamentals
• Statistical analysis and anomaly detection
• Test case development and regression testing
• Dashboard development and data quality reporting
• Process improvement and quality assurance methodologies

Work Authorization

• US Citizens or Green Card holders
• On F-1 OPT or STEM-OPT
• Eligible for or currently holding H-1B status

Work authorization and sponsorship arrangements are subject to client engagement requirements.

Compensation & Benefits

• Market-competitive salary: $70,000–$100,000/year, depending on client, location, experience, and qualifications.
• Health and wellness benefits through placement, where offered by the client or employer.
• Paid Time Off (PTO), where applicable.
• Ongoing learning and professional development support.
• Exposure to real-world data quality, data validation, and analytics projects.
• Opportunities to work with databases, cloud data platforms, and enterprise data systems.
• Experience collaborating with data engineering, business intelligence, QA, and data governance teams.
• Opportunities to develop skills in SQL, data analysis, quality automation, and data management.