Data Quality Analyst

TL;DR

Data Quality Analyst: Ensuring the accuracy, completeness, consistency, and reliability of data assets with an accent on data profiling, validation, cleansing, and data governance. Focus on building data quality metrics, monitoring pipelines for anomalies, and performing root-cause analysis to improve data integrity across systems.

Location: North Andover, MA (office three days per week; remote two days per week)

Salary: $24.00 - $30.00/hr

Company

hirify.global builds smart and connected water solutions for residential and commercial customers.

What you will do

• Perform data profiling, validation, and cleansing to maintain high-quality datasets.
• Identify, investigate, and resolve data discrepancies and anomalies.
• Develop and maintain data quality metrics, rules, and dashboards.
• Monitor data pipelines and systems for consistency and accuracy.
• Support root cause analysis of data defects and recommend corrective actions.
• Document data quality standards and participate in data governance initiatives, including audits.

Requirements

• Bachelor’s degree in data analytics, computer science, information systems, or a related field.
• 2+ years of experience in data quality, data analysis, or similar roles.
• Strong SAP skills and experience working with relational databases.
• Proficiency in Excel and data visualization tools (Power BI, Tableau).
• Strong analytical, problem-solving, and critical-thinking skills with excellent attention to detail.

Culture & Benefits

• Comprehensive medical and dental coverage and retirement benefits.
• Paid time off, including 10 paid holidays.
• Family building benefits, including paid maternity/paternity leave.
• Professional development opportunities and educational reimbursement.
• Fitness reimbursements and employee discount programs.
• Team-oriented, supportive culture focused on integrity, accountability, continuous improvement, and transparency.

Hiring process

• Interviews to evaluate experience with data quality, SAP, and analytics tools.
• Discussion of collaboration with cross-functional stakeholders and data governance responsibilities.