Role & seniority: Data Quality Assurance Engineer (mid-level; 2+ years in Data QA/Data Engineering QA)

Stack/tools: SQL (advanced, complex queries, performance optimization), Python (test data creation, automation, data analysis), open-source SQL engines, data validation/reconciliation, analytics platforms; familiarity with HIPAA compliance

Top 3 responsibilities

Validate, test, and ensure quality of large, complex datasets across systems and analytics applications
Write/execute complex SQL queries and use Python to generate test data and automate validation of data pipelines
Review requirements/design docs, create test datasets/outputs, perform regression/integration testing, document defects and verify fixes

Must-have skills

Bachelor’s in CS/Engineering/IT/Information Management or related field
2+ years in Data QA or Data Engineering QA
Advanced SQL skills (joins, aggregations, performance tuning) and Python proficiency
Data analysis, data validation, QA methodology, and ability to design test cases for data-driven systems
Experience with data security/privacy/compliance (HIPAA) and communicating technical findings

Nice-to-haves

Healthcare experience (US) prior to or in addition to QA experience
Analytics applications familiarity and operating with analytics platforms
Strong written and verbal communication; collaboration with cross-functional teams
Location & work type: Location not specified; work type not sta

Full Description

Job Title

Data Quality Assurance Engineer

Job Summary

We are seeking a Data Quality Assurance (QA) Engineer with strong expertise in data analysis, SQL, and Python to ensure the accuracy and integrity of our data systems. This role involves validating large datasets, preparing and generating test data, and verifying data processing logic across analytics applications.

The ideal candidate will bring strong analytical skills and hands-on experience in testing and validating complex datasets to maintain the highest standards of data quality.

Job Description

As a Data QA Engineer, you will be responsible for validating, testing, and ensuring the quality of large, complex datasets used in our products and analytics platforms.

Your responsibilities will include

Reviewing requirements, specifications, and data logic design documents to provide valuable feedback to stakeholders.
Writing and executing complex SQL queries to validate data and ensure correctness.
Using Python for test data creation, data analysis, automation, and validation of data pipelines.
Preparing test datasets and creating expected outputs to validate data processing logic.
Conducting thorough data validation and reconciliation across multiple systems and data flows.
Performing regression and integration testing on large-scale datasets.
Working with open-source SQL engines, interpreting their documentation to understand query logic, and ensuring correct implementation and integration with application workflows.
Ensuring adherence to data security, privacy, and compliance requirements (HIPAA).
Collaborating with developers, product managers, and business analysts to ensure requirements are met and quality is maintained.
Identifying, documenting, and tracking data-related defects, and validating fixes.
Applying strong analytical and troubleshooting skills to resolve complex data quality issues.
Contributing to continuous improvement of QA processes and strategies for data-focused projects.
Preparing clear and detailed QA documentation and communicating findings effectively to technical and non-technical stakeholders.

Job Specification

Required Skills and Expertise

Education: A Bachelor's degree in Computer Science, Engineering, Information Technology, Information Management, Computer Application, or a related field.

Experience: Minimum 2+ years of experience in Data QA or Data Engineering QA roles.

Data Quality Assurance Engineer