Data Engineer – Google Cloud Platform (GCP)
Why Keyrus, Why Now!
Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.
For more than 30 years, we have helped organizations build the data foundations that power intelligent systems. Today, we go further by designing and operationalizing intelligence that delivers measurable business value.
Building reliable data platforms is essential to enabling intelligent business operations. Real transformation happens when data flows seamlessly across systems, applications, and business processes.
At Keyrus, you'll work with modern cloud technologies to develop scalable data solutions, support critical enterprise systems, and help organizations transform complex data into measurable business value.
Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.
Role details
As a Data Engineer – Google Cloud Platform (GCP), you'll design, develop, and maintain cloud-based data ingestion processes and pipelines that support enterprise data operations.
You'll work with BigQuery, Google Pub/Sub, Dataform, Cloud Storage, and Cloud Composer to build reliable, scalable, and efficient data solutions aligned with business requirements and technical architecture specifications.
Your focus goes beyond developing pipelines. You'll ensure data reliability, troubleshoot production issues, optimize existing workflows, and contribute to the continuous improvement of cloud data environments.
Your Responsibilities
You are a hands-on Data Engineer who enjoys building reliable and scalable cloud data solutions. You have experience working with Google Cloud Platform and understand how to design, develop, and maintain data pipelines that support business-critical operations. You are comfortable working independently, collaborating with distributed teams, and troubleshooting technical challenges. You combine analytical thinking, problem-solving skills, and attention to detail with a strong commitment to data reliability, performance, and engineering best practices.
Experience
What you bring
At Keyrus, we help organizations move from experimental to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution.
As Architects of Intelligence, we design the Operating System of the intelligent enterprise, embedding intelligence into business processes so that it creates sustainable, measurable value.
Powered by our proprietary Human Orchestrated Model (HOM), we architect reliable:
AI does not transform businesses. Architected intelligence does.
For more information: www.keyrus.com
Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.
For more than 30 years, we have helped organizations build the data foundations that power intelligent systems. Today, we go further by designing and operationalizing intelligence that delivers measurable business value.
Building reliable data platforms is essential to enabling intelligent business operations. Real transformation happens when data flows seamlessly across systems, applications, and business processes.
At Keyrus, you'll work with modern cloud technologies to develop scalable data solutions, support critical enterprise systems, and help organizations transform complex data into measurable business value.
Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.
Role details
- Location: Remote – Colombia
- Contract: Permanent employment contract.
- Working hours: Eastern Time (ET)
As a Data Engineer – Google Cloud Platform (GCP), you'll design, develop, and maintain cloud-based data ingestion processes and pipelines that support enterprise data operations.
You'll work with BigQuery, Google Pub/Sub, Dataform, Cloud Storage, and Cloud Composer to build reliable, scalable, and efficient data solutions aligned with business requirements and technical architecture specifications.
Your focus goes beyond developing pipelines. You'll ensure data reliability, troubleshoot production issues, optimize existing workflows, and contribute to the continuous improvement of cloud data environments.
Your Responsibilities
- Design, develop, and maintain scalable data ingestion pipelines and workflows using Google Cloud Platform.
- Implement and optimize data processing and transformation solutions using BigQuery, Dataform, Pub/Sub, Cloud Storage, and Cloud Composer.
- Develop SQL queries to extract, transform, validate, and troubleshoot data across enterprise systems.
- Build and maintain ingestion processes that integrate data from multiple sources into BigQuery.
- Troubleshoot pipeline failures, data inconsistencies, and production issues to ensure operational stability.
- Develop and execute unit, system, integration, and user acceptance testing, documenting results and ensuring solution quality.
- Collaborate with engineering teams, architects, and business stakeholders to translate requirements into effective technical solutions.
- Participate in technical design discussions, code reviews, project planning, and continuous improvement initiatives.
- Prepare and maintain technical documentation, development specifications, and implementation plans.
- Follow security, data governance, and engineering standards when handling sensitive information.
- Participate in an on-call production support rotation, typically one full week every 4–6 weeks, depending on staffing availability.
You are a hands-on Data Engineer who enjoys building reliable and scalable cloud data solutions. You have experience working with Google Cloud Platform and understand how to design, develop, and maintain data pipelines that support business-critical operations. You are comfortable working independently, collaborating with distributed teams, and troubleshooting technical challenges. You combine analytical thinking, problem-solving skills, and attention to detail with a strong commitment to data reliability, performance, and engineering best practices.
Experience
What you bring
- 3+ years of professional experience in data engineering, data integration, or related technical roles.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Experience designing, developing, and maintaining cloud-based data ingestion pipelines.
- Experience implementing and supporting data processing workflows in Google Cloud Platform environments.
- Experience troubleshooting production data pipelines and resolving data quality or integration issues.
- Familiarity with software development practices, testing methodologies, and technical documentation.
- Ability to work independently and collaborate effectively with technical teams and business stakeholders.
- Hands-on experience with Google Pub/Sub for event-driven messaging and data ingestion.
- Strong knowledge of BigQuery for data warehousing, querying, and processing.
- Experience with Google Dataform for SQL-based data transformations and workflow management.
- Experience designing and implementing data ingestion processes into BigQuery from multiple sources.
- Experience with Google Cloud Storage for cloud-based data storage and integration.
- Knowledge of Cloud Composer (Apache Airflow) for workflow orchestration and scheduling.
- Experience using GitHub for version control and collaborative development.
- Strong SQL skills for data querying, transformation, validation, and troubleshooting.
- Experience with Google Cloud Data Fusion.
- Experience connecting to and interacting with relational databases such as SQL Server, DB2, or Oracle.
- Experience consuming and integrating RESTful APIs and SOAP web services.
- Familiarity with additional Google Cloud services, databases, and enterprise integrations.
- Experience using Jira and Confluence for project management and documentation.
- Previous experience working in the retail industry.
- You design and deliver reliable, scalable, and maintainable data pipelines.
- You identify and resolve production issues efficiently, ensuring data availability and operational stability.
- You collaborate effectively with technical teams and stakeholders to deliver high-quality solutions.
- You take ownership of your work while following engineering, security, and documentation standards.
- You continuously identify opportunities to improve data workflows, performance, and operational efficiency.
- A stimulating environment where you can challenge yourself and discover new horizons.
- A strong culture of innovation and entrepreneurship.
- Opportunities to work on enterprise-scale data engineering projects using modern cloud technologies.
- All mandatory Colombian employment benefits and statutory entitlements, in accordance with applicable labor legislation.
- A fully remote working arrangement, aligned with Eastern Time working hours.
- Opportunities for professional growth, collaboration, and continuous learning.
At Keyrus, we help organizations move from experimental to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution.
As Architects of Intelligence, we design the Operating System of the intelligent enterprise, embedding intelligence into business processes so that it creates sustainable, measurable value.
Powered by our proprietary Human Orchestrated Model (HOM), we architect reliable:
- Intelligence Foundations
- Human in Command governance
- Performance Steering
AI does not transform businesses. Architected intelligence does.
For more information: www.keyrus.com
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