Quality Engineer – Data Quality & Cloud Analytics Platforms

Why Keyrus, Why Now!

Keyrus is an international group of 2,800 consultants and experts across 28 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does. For more than 30 years, we have been building the data foundations that make intelligent systems work — designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalise intelligence.

AI does not replace humans. It repositions us to a place no system can follow: understanding, deciding, designing, and creating. At Keyrus, you will not just develop skills—you will develop judgment. Your expertise sharpens with every client challenge you solve, every opportunity you shape, and every strategic partnership you help build.

Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges business strategy, data, AI, and executive decision-making at scale. This is not a role you fill. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

🚀 What You'll Architect

As aQuality Engineer within Keyrus's Enterprise Data Platform practice, you will architect the trust behind the data by building validation frameworks, automated testing solutions, and quality controls that ensure enterprise data products are accurate, reliable, and ready to drive business decisions.

You will operate across ingestion, transformation, storage, and processing layers of complexGoogle Cloud Platform (GCP) analytics environments, working closely with Data Engineers, Cloud Architects, and Data Analysts to embed quality throughout the entire data lifecycle.

You will:

• Validate data across ingestion, transformation, integration, and processing workflows in GCP environments to ensure quality, accuracy, and consistency.

• Perform source-to-target validation and reconciliation across multiple systems, includingBigQuery,Cloud Storage,Cloud SQL, and external data sources.

• Verify business rules, data mappings, transformations, and data lineage throughout cloud-based data pipelines.

• Ensure compliance with key data quality dimensions including completeness, accuracy, consistency, timeliness, validity, uniqueness, and referential integrity.

• Design, develop, execute, and maintain automated and manual testing frameworks for data validation across GCP data ecosystems.

• Implement reusable quality controls and automated testing processes integrated into CI/CD pipelines using tools such asCloud Build,GitHub Actions,GitLab CI/CD, or similar platforms.

• Create and maintain test cases, validation rules, test scenarios, quality metrics, and testing documentation.

• Continuously identify opportunities to automate manual testing processes and improve testing efficiency.

• Support enterprise data platforms built onGoogle Cloud Platform, includingBigQuery,Dataflow,Cloud Composer (Apache Airflow),Pub/Sub,Dataproc, andCloud Storage.

• Validate ELT/ETL pipelines developed using modern cloud-native data engineering frameworks.

• Monitor pipeline execution, orchestration workflows, scheduling processes, and quality controls to proactively identify and resolve issues.

• Collaborate with Data Engineering and Cloud teams to ensure successful deployment of new data products and platform capabilities.

• Investigate data discrepancies, pipeline failures, and quality issues through root cause analysis.

• Manage defects through their full lifecycle, from identification and documentation through validation and closure.

• Conduct regression testing to ensure new changes do not negatively impact existing data assets and analytics products.

• Participate in User Acceptance Testing (UAT) activities with business stakeholders and technical teams.

• Support release readiness reviews, quality gate assessments, and post-release validation activities.

• Contribute to the establishment and continuous improvement of enterprise data quality standards, testing methodologies, and best practices.

🧠 Who You Are

• You see data quality as the foundation of trust, not a checkbox at the end of the pipeline

• You naturally connect technical validation with business impact, understanding what "accurate" really means for decision-makers

• You are comfortable engaging engineers, architects, and business stakeholders to align on data standards and expectations

• You thrive in environments where precision, curiosity, and automation-minded thinking create competitive advantage

• You balance rigorous testing discipline with a genuine interest in improving how teams deliver quality at scale

• You enjoy working alongside data engineers and architects to shape reliable, production-grade data products

• You bring an entrepreneurial mindset and proactively surface quality risks rather than waiting for them to surface downstream

🛠️ What You Bring

Qualifications / Certifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience

• 4+ years of experience in Data Quality Engineering, Data Testing, Quality Assurance, or similar roles supporting enterprise data platforms

Technical Skills

• Strong SQL skills with experience validating, reconciling, and analyzing large and complex datasets

• Strong experience with Google Cloud Platform (GCP), including technologies such as BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage

• Hands-on experience working with modern cloud-based data platforms and analytics ecosystems

• Strong understanding of ETL/ELT processes, data modeling concepts, dimensional modeling, and data architecture principles

• Experience developing and executing automated data validation and testing frameworks

• Familiarity with CI/CD practices and integrating quality controls into software and data delivery pipelines

• Experience documenting test cases, validation rules, defects, and quality processes using collaboration and project management tools

• Excellent analytical, troubleshooting, and problem-solving skills

• Strong written and verbal communication skills, with the ability to explain technical issues to both technical and business audiences

⭐Nice-to-haves

• Experience supporting enterprise cloud migration, data modernization, or data warehouse transformation initiatives

• Knowledge of data observability, monitoring, and data governance concepts

• Working proficiency in Python or other scripting languages used for test automation and data validation

• Experience working within Agile delivery environments and large-scale data transformation programs

• Experience supporting analytics, customer insights, marketing, or business intelligence platforms

🎯 What Makes You Successful

• Exceptional attention to detail and an unwavering commitment to data accuracy

• A proactive and collaborative approach to solving complex, cross-functional data challenges

• Strong communication and stakeholder management skills, with advanced English proficiency (written and spoken)

• The ability to work effectively in fast-paced environments with multiple concurrent initiatives

• A continuous improvement mindset focused on automation, efficiency, and delivery excellence

• Availability to collaborate with distributed teams operating in Eastern Time (EST)

Role Details

• Location: Colombia

• Contract: Full-time, indefinite term

• Work Model: 100% Remote

• Level: Mid Level to Semi senior

Rewards - What We Offer at Keyrus

• 100% remote work

• International and multicultural projects

• Opportunities to work with leading technologies in the Digital Commerce ecosystem

• Access to training programs and continuous professional development

• Professional growth opportunities and internal mobility

• A culture built on collaboration, innovation, and continuous learning

🌍What We Stand For

• Collective Intelligence — Collaboration across expertise, functions, and geographies makes it possible to combine know-how and deliver more comprehensive responses to client challenges.

• Reliability — The ability to deliver complex projects with rigour is one of the pillars of our client relationship.

• Pragmatism — Prioritising concrete impact and measurable value over abstract technological discourse.

• Entrepreneurial Spirit — Curiosity, energy, and freedom are the foundations of our culture; they enable initiative and sustained innovation.

ABOUT KEYRUS

At Keyrus, we help organizations move from experimental AI to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution. This is the discipline we call being an Architect of Intelligence. Designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalize intelligence.

Powered by our proprietary Human Orchestrated Model™ (HOM), we architect reliable:

• Intelligence Foundations

• Human in Command governance

• Performance Steering

To create intelligent environments where technology amplifies human capabilities and performance compounds over time.

With 30+ years of expertise and 2,800 employees across 28 countries, we help organizations go beyond transformation: to build adaptive, resilient, and continuously improving intelligent organizations.

AI does not transform businesses. Architected intelligence does.

Keyrus is listed on Euronext Growth Paris. (ALKEY – ISIN Code: FR0004029411 – Reuters:KEYR.PA – Bloomberg: ALKEY: FP).

For more information:www.keyrus.com