Senior Data Quality Engineer

WHAT WE DO Founded in 2007, Growth Acceleration Partners (GAP) is a premier consulting and technology services company built for the AI era. We consult, design, build, and modernize revenue-generating software and data engineering solutions. By leveraging AI-native architectures, advanced data analytics, and deep modernization strategies, we help businesses secure a competitive advantage. GAP’s remote, integrated engineering teams deliver end-to-end solutions that drive true business innovation. We are a woman-owned, Austin-based company with over 600 English-speaking engineers across Latin America and the U.S. Boasting industry-leading customer satisfaction scores, our core focus is the dual success of our clients and our people. We are a values-based organization deeply invested in the growth of our "GAPsters"—providing continuous education, onsite English classes, and cutting-edge training in AI, machine learning, and next-gen technologies to ensure our communities achieve long-term success. Summary We are looking for a Senior Data Quality Engineer with strong expertise in validating data pipelines, ETL processes, and enterprise Data Warehouse environments. In this role, you will be responsible for ensuring the integrity, reliability, and consistency of the data powering analytics and reporting platforms . The primary focus of this position is validating the quality of data as it moves across pipelines, transformations, and warehouse layers. You will work closely with Data Engineers and Data Analysts to analyze datasets, review ETL pipelines, validate transformations, and detect anomalies within analytical data environments. This role requires a strong analytical mindset and a deep understanding of how data flows across systems and integrations. This is not a traditional QA role focused on application testing or BI dashboards. Instead, it is a data-focused role centered on validating the quality, completeness, and accuracy of analytical datasets before they are consumed by reporting or analytics systems. Education Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related technical field. Professional Experience 5+ years of experience working with data validation, data quality, or data pipeline reliability Strong grasp of Quality Assurance lifecycle (SDLC) and industry-standard testing protocols Proven experience working with Data Warehouse and analytical data models Hands-on experience validating ETL pipelines and data integrations. Key Responsibilities Data Quality & Data Warehouse Validation Ensure the accuracy, completeness, and consistency of data entering the Data Warehouse Validate analytical datasets and data models across layers Perform reconciliation and cross-validation between data layers ETL & Data Pipeline Validation Review and validate ETL pipelines and data integrations feeding Data Lakehouses Analyze ingestion workflows and transformation logic across data pipelines Validate transformations across staging, processing, and warehouse layers Perform source-to-target data validation across environments Ensure pipelines deliver high-quality datasets to downstream analytics systems Data Investigation & Validation Write advanced SQ L queries to validate datasets and transformations Investigate discrepancies across multiple data sources Identify anomalies, unexpected patterns, or data inconsistencies Perform root cause analysis on data quality issues across systems Automation & Data Validation Frameworks Develop automated data validation processes using Python Implement repeatable validation checks across data pipelines Build monitoring checks for data completeness and integrity Integrate validation processes into CI/CD pipelines Cross-Functional Collaboration Partner with Data Engineers and Data Analysts to maintain reliable analytical datasets Support validation activities before data is consumed by analytics platforms or reporting tools Collaborate with governance teams to maintain data quality standards Document validation rules, processes, and methodologies Required Technical Skills Strong SQL expertise for data validation and troubleshooting Experience working with Data Lakehouses and analytical data models Hands-on experience validating ETL pipelines and data integrations Experience in Data Quality validation across analytical datasets Ability to define, enforce, and optimize QA workflows to ensure high-quality delivery Basic Python skills for data processing and validation Deep understanding of data flows across systems and integrations Strong analytical mindset with Data Engineer / Data Analyst perspective Experience identifying anomalies and inconsistencies in large datasets Experience integrating data validation into CI/CD pipelines Nice to Have Experience working with Microsoft Fabric Familiarity with Databricks Working knowledge of A zure Data Factory or similar orchestration tools Exposure to Great Expectations for data validation Soft Skills Advanced English proficiency (spoken and written) Strong analytical and investigative mindset Excellent documentation and communication skills Ability to identify risks and proactively address data quality issues Collaborative mindset when working with data and engineering teams Strong attention to detail and problem-solving abilities At Growth Acceleration Partners, we're an equal opportunity employer committed to building a diverse and inclusive team. We value everyone's unique background, and we provide equal opportunities regardless of race, color, creed, religion, sexual orientation, gender identity, age, national origin, disability, marital status, veteran status or any other personal right protected by law. We foster a culture of belonging and strive to provide a welcoming environment where everyone feels safe to contribute and grow.