Quality Engineer – Data Quality & Cloud Analytics Platforms

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 a Quality Engineer within Keyrus's Enterprise Data Platform practice, you will architect the trust behind the data — building the validation frameworks, testing automation, and quality controls that ensure enterprise data products are accurate, reliable, and ready to drive business decisions. You will operate across ingestion, transformation, and processing layers of complex cloud analytics environments, working shoulder-to-shoulder with data engineers and architects to embed quality into the core of every pipeline, not as an afterthought but as an engineered discipline.

You Will Validate data across ingestion, transformation, integration, and processing workflows to ensure quality, accuracy, and consistency

Perform source-to-target validation and reconciliation across multiple systems and data platforms

Verify business rules, data mappings, transformations, and data lineage throughout the data lifecycle

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

Implement reusable quality controls and automated testing processes integrated into CI/CD pipelines

Create and maintain test cases, validation rules, test scenarios, and quality documentation

Continuously identify opportunities to automate manual testing and improve testing efficiency

Support enterprise data platforms built on modern cloud technologies and large-scale data ecosystems

Validate data pipelines, orchestration workflows, scheduling processes, and integration components

Monitor pipeline execution and quality controls to proactively identify and resolve issues

Collaborate with engineering teams to ensure the successful deployment of new data products and platform capabilities

Investigate data discrepancies, pipeline failures, and quality issues; perform 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 functionality

Participate in User Acceptance Testing (UAT) activities in partnership with business and technical teams

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

Contribute to the establishment and continuous improvement of quality standards, testing methodologies, and best practices

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

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

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

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

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

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)

Location: Colombia

Contract: Full-time, indefinite term

Work Model: 100% Remote

Level: Mid Level to Semi senior

Rewards - What We Offer At Keyrus 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:

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).

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