DATA QUALITY ENGINEER

Role Overview

We are seeking a detail-oriented and analytical Data Quality Engineer with 2+ years of experience to ensure the accuracy, completeness, consistency, and reliability of data across our AI-driven healthcare platforms. This role will be responsible for designing and executing data quality strategies, validating data pipelines, and collaborating closely with data engineering, data science, and product teams to deliver high-quality data assets in a fast-paced environment.

Key Responsibilities

·       Design, develop, and execute comprehensive data quality test plans, test cases, and validation scripts

·       Perform data validation testing across ETL/ELT pipelines, databases, and data warehouses

·       Validate data accuracy, completeness, consistency, uniqueness, and timeliness across data systems

•  Health Insurance/HMO 
•  Enjoy unlimited MadMax Coffee
•  Diverse learning & growth opportunities
•  Accessible Cloud HR platform (Sprout)
•  Above standard leaves

·       Collaborate with Business teams and product managers to understand data requirements and define data quality acceptance criteria

·       Identify, document, and track data quality issues using standard defect tracking tools

·       Develop and maintain automated data quality tests and validation frameworks

·       Validate data transformations, aggregations, and business logic within data pipelines

·       Test and validate database schemas, data models, and data integration processes

·       Profile data sources to identify data quality patterns, anomalies, and improvement opportunities

·       Monitor data quality metrics and create dashboards to track data health over time

·       Participate in sprint planning, stand-ups, and release discussions with data and engineering teams

·       Ensure data quality aligns with business requirements, regulatory standards, and user expectations

·       Contribute to continuous improvement of data quality processes, standards, and best practices

Required Experience & Skills

·       2+ years of professional experience in Data Analyst, Data Testing, or Data Analysis

·       Strong understanding of data quality dimensions (accuracy, completeness, consistency, validity, timeliness)

·       Experience with SQL and database testing (PostgreSQL, MongoDB, or similar)

·       Hands-on experience testing ETL/ELT data pipelines and data transformations

·       Familiarity with data quality automation tools and frameworks (Great Expectations, dbt tests, or similar)

·       Experience with data profiling, anomaly detection, and data validation techniques

·       Basic understanding of data engineering concepts, data warehousing, and data modeling

·       Experience working in Agile/Scrum environments with data and engineering teams

·       Strong analytical, problem-solving, and debugging skills

·       Excellent communication and documentation skills

Preferred:

·       Exposure to AI-driven or data-centric platforms and ML data pipelines

·       Experience with healthcare or clinical data standards (CDISC, HL7, FHIR)

·       Familiarity with vector databases and RAG pipeline data validation

·       Experience with Python or scripting for data validation automation

·       Knowledge of data governance frameworks and data privacy regulations (GDPR, HIPAA)

·       Experience with API testing tools such as Postman for data API validation

·       Basic knowledge of CI/CD pipelines and DevOps practices for data systems

Work Culture & Expectations

·       Startup-lean environment with enterprise-grade data quality standards

·       High ownership role with accountability for data quality and data reliability

·       Strong collaboration across data engineering, data science, product, and AI teams

·       Continuous learning mindset with focus on automation and data quality innovation

·       Bias toward execution, attention to detail, and proactive problem-solving

·       Data-first mindset with emphasis on data integrity and trustworthy AI systems

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