🎁 Antes de postularte, practica esta entrevista. Crea tu cuenta gratis en WorkMundi y recibe un Entrenamiento de Entrevista en HelpsYouSpeak — sin costo, sin tarjeta. Quiero mi entrenamiento →
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 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 🧠 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 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 Strong experience with Google Cloud Platform (GCP), including technologies such as BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.